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Assessing the Requirements for Power
Performance Testing at the National Small
Wind Turbine Centre Test Site
Supervised By
Dr. Jonathan Whale
Submitted by
Avishek Malla
30775829
i
Declaration The following study is based on author’s own assessment in recommending the
National Small Wind Turbine Centre (NSWTC) to carry out power performance test
of small wind turbine at their test facility. The work relied on others, during the study
is appropriately acknowledged in the report.
ii
Acknowledgement
I would like to thank my supervisor Dr. Jonathan Whale, for guiding me throughout
this dissertation. I would like to thank Mr. Colin Black, Mr. Daniel Jones and Mr.
Bernie Brix for their valuable advices and support. I would also like to thank the
Bureau of Meteorology and Jandakot Airport for providing useful data for WAsP
modelling.
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Abstract This report aims to recommend National Small Wind Turbine Centre (NSWTC), the
preliminary requirements to conduct the power performance test of Small Wind
Turbines in accordance to the IEC61400-12-1 standard. It also investigates the
availability of wind resource at the test site, which will assist to manage testing
schedule by developing wind predicting models using WAsP software. The
objectives of the project are-
1st objective –Assessing the requirements for power performance testing
• Checking test site compatibility with the IEC61400-12-1 standard
• Recommending brands of monitoring instruments by using the
IEC61400-12-1 standard and IEA proposed selection criteria
• Recommending appropriate designing for positioning of monitoring
instruments by using the IEC61400-12-1 standard as a tool
2nd objective – Assessing the test site limitations to identify factors that will assist to
manage the power performance test schedule at the test site such as-
• Types of turbines that can be tested, which meet the criteria set by the
IEC61400-12-1 and the BWEA standard
• Suitable times of the year for testing to satisfy the criteria set by
IEC61400-12-1 and the BWEA standard
• Overall length of time required to complete the test in accordance to
the IEC61400-12-1 and the BWEA standard
The report concludes that –
• Site calibration at the NSWTC test site is required in order to comply with the
IEC61400-12-1 standards.
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• Some of the monitoring instruments have to be repurchased to test in
accordance to the IEC61400-12-1 standard. For example- NSWTC should
reconsider purchasing a cup anemometer with a class type better than 1.7A,
to comply with IEC61400-12-1.
• The mountings of monitoring instruments can be arranged without major
modification to test up to a 5 meter rotor diameter turbine. Beyond this,
special arrangements have to be made such as laying out a new concrete
foundation for a meteorological mast.
• The WAsP prediction results show, power performance tests can only be
carried out on a limited range of wind turbines because the required wind
bins are highly unlikely to be complete for turbines falling outside the range.
Further, the predicted wind bins for individual months of the year should be
considered for approximating a time period of the test, selecting a suitable
month to begin the test and also for preparing test schedules of different
turbines over a year.
In the absence of real data at the test site, it is recommended that NSWTC should
initially consider the predicted results when selecting turbines for testing. Future
decisions on turbine selection should be based on the meteorological data collected at
the site over at least a year in conjunction with the WAsP model.
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1 Introduction ....................................................................................................................................... 1
1.1 Background ............................................................................................................................. 1 1.2 The National Small Wind Turbine Centre (NSWTC) ............................................. 3 1.3 Research Questions ............................................................................................................. 5 1.4 Objective of the Project ...................................................................................................... 5 1.5 Scope of the Project ............................................................................................................. 6 1.6 Overview of the methodology ............................................................................................ 6 1.7 Dissertation Structure ........................................................................................................ 7
2 Methodology ..................................................................................................................................... 8 2.1 Methodology to First Objective ......................................................................................... 8 2.2 Methodology to Second Objective ................................................................................... 9
3 Literature Review .......................................................................................................................... 11 3.1 Literature Review for Assessing Site Requirements ................................................ 11 3.2 Literature Review for Assessing Instrument Requirements ................................... 12
3.2.1 IEC61400-12-1 Recommendations on Instruments ......................................... 13 3.2.2 Parameters for Turbine Power Performance Testing Proposed by IEA Task 27 ....................................................................................................................................... 15
3.3 Literature Review for Mounting and Arrangements of Monitoring Instruments ............................................................................................................................................................ 16 3.4 Literature Review Assessing the Test Site Limitations ........................................... 18
4. NSWTC Test Facility ................................................................................................................. 21 4.1 Installation of Preliminary Wind Monitoring System .............................................. 21
4.1.1 Data from Preliminary Wind Monitoring ............................................................ 23 4.2 Installation of Wind Turbine Tower and Meteorological Mast ............................ 25 4.3 NSWTC Test Site Requirements ..................................................................................... 26
5 Monitoring Instruments for Power Performance Testing ................................................ 30 5.1 Instruments for Meteorological Parameters ................................................................. 30 5.2 Recommendations on Meteorological Measuring Instrument ............................... 34 5.3 Instrument for Electric Parameter ................................................................................... 35 5.4 Instrument for Data Acquisition ...................................................................................... 36 5.5 Bench Testing ........................................................................................................................ 37 5.6 Arrangement and Mounting of the Monitoring Instruments .................................. 40
6. Predicting Wind Resource at NSWTC Using WAsP Modelling ................................. 43 6.1. Considerations for Selection of a Reference Site ..................................................... 45
6.1.1. Length of Data Available ......................................................................................... 45 6.1.2 Nearest to Similar Terrains ....................................................................................... 46 6.1.3 Least Obstructed Site .................................................................................................. 46 6.1.4 Data Quality ................................................................................................................... 46
6.2 Identification and Selection of Reference Site ........................................................... 47 6.3 Data Handling ........................................................................................................................ 48 6.4 WAsP Modelling .................................................................................................................. 50
6.4.1 Data Preparation ........................................................................................................... 51 6.4.2 Creating Wind Atlas.................................................................................................... 51
6.5 Predicting Wind resource at NSWTC ............................................................................ 57 6.5.1 Roughness Rose for NSWTC .................................................................................. 57 6.5.2 Obstacle Lists for NSWTC Testing Site .............................................................. 59
6.6 WAsP Results ........................................................................................................................ 59 6.7 WAsP Model Validation .................................................................................................... 60
6.7.1 Data Preparation for Validation .............................................................................. 61 6.7.2 Results .............................................................................................................................. 61
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6.7.3 Comparison between Results Obtained from Predicted and Real Measurements .......................................................................................................................... 63
7. Assessing NSWTC Test Site Limitations ............................................................................ 68 8. Discussion & Recommendations ............................................................................................ 77
8.1 Summary of Recommendations ....................................................................................... 79 8.2 Future Work ........................................................................................................................... 80
9. Conclusion ...................................................................................................................................... 81 10 References ..................................................................................................................................... 83 11 Appendix ....................................................................................................................................... 85
Appendix A Site Requirements ............................................................................................... 85 A1 Scoring Criteria for Site Assessment ........................................................................ 85 A2 Survey Map for NSWTC Test Site ............................................................................ 85
Appendix B Monitoring Instruments .................................................................................... 87 B1. Davis Instrument ............................................................................................................. 87 B2 Cup Anemometer ............................................................................................................. 88 B3 Wind Vane .......................................................................................................................... 97 B4 Temperature and Humidity Sensor ......................................................................... 101 B5 Pressure Sensor .............................................................................................................. 105
Appendix C Measurement at NSWTC Test Site ............................................................ 112 C1 Wind Rose Measured at NSWTC Presented in Tabular Format ................... 112
Appendix D WAsP Related ................................................................................................... 113 D1. Reference Sites Investigated for WAsP ............................................................... 113 D1.1 Missing Contours of the Site ................................................................................. 120 D2 WAsP Wind Rose ......................................................................................................... 120 D3 Predicted Wind Bins by calculating the Weibull Probability Density Function (using data -September – December 2009) ............................................... 121 D4 Annual Predicted Wind Speed Bins for NSWTC Test Site at 12m, 18m and 24m using the Weibull Probability Density Function ............................................. 122 D5. WAsP Predicted Wind-Bins Tables at 18magl for Each Individual Month at NSWTC Test Site ................................................................................................................ 125 D6 Buildings with their Respective Heights Located at Jandakot Airport ....... 130 D7 Roughness Values Suggested by the European Wind Atlas Based on Characteristic of the Terrain Type.................................................................................. 132
Appendix E Bench Testing .................................................................................................... 133 E1. Data logger Program for the Monitoring Equipments During Bench Test .................................................................................................................................................... 133 E2. Graphs of Sensor Recordings During the Bench Test ..................................... 134
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List of Figures Figure 1 Showing the areas to be assessed during site calibration in accordance to
IEC 61400-12-1 Annex B (IEC, 2005, p. 36) ................................................................ 11 Figure 2 Showing the measurement sectors that has to be excluded during analysis of
data (IEC, 2005, p. 15) .......................................................................................................... 17 Figure 3 Extracted from IEC61400-12-1 showing the arrangement of monitoring
instruments on a boom(IEC, 2005, p. 69) ....................................................................... 17 Figure 4 Showing the location of NSWTC test site (Courtesy: Google Earth) ........... 21 Figure 5 Series of snap shots taken during the installation of the preliminary
monitoring system and the mast (Courtesy: NSWTC) ............................................... 23 Figure 6 Wind rose diagram prepared from the preliminary measurements recorded
at NSWTC ................................................................................................................................. 24 Figure 7 Series of snap shots taken during the installation of the preliminary
monitoring system and the mast (Courtesy: NSWTC) ............................................... 26 Figure 8 Shows an enlarged section on the NSWTC site map ..................................... 27 Figure 9 AWT190 power transducer with class of 0.2 (Courtesy NSWTC) ................ 35 Figure 10 Picture of DT80 ............................................................................................................. 36 Figure 11 Bench testing setup of the monitoring equipments ........................................... 38 Figure 12 Flow diagram of sensor connection to the data-logging unit ......................... 39 Figure 13 Top view of the recommended instrument mounting arrangement ............ 41 Figure 14 Side view of boom mounting with recommended distances from
instrument arrangements to meet the IEC61400-12-1 standard .............................. 42 Figure 15 showing WAsP methodology (Petersen et. al.,1989, p.17) ...................... 44 Figure 16 Showing location of NSWTC test facility along with the three short listed
sites (Courtesy – Google Earth) ......................................................................................... 47 Figure 17 Column 'F' showing recordings at other than 30 minutes interval, such
data were filtered out ............................................................................................................. 49 Figure 18 Showing the vector map with 5meter contour intervals used for analysis in
WAsP .......................................................................................................................................... 52 Figure 19 A 10km radius circle with centre at Jandakot met-station divided into 12
equal parts to analyse the surface roughness in each parts ....................................... 53 Figure 20 Roughness rose prepared for the Jandakot airport based on Google Earth
image and European Wind Atlas ....................................................................................... 54 Figure 21 Buildings with their respective heights located at Jandakot airport
(Courtesy Jandakot Airport) ................................................................................................ 55 Figure 22 Showing how to measure various parameters listed in table 9 to locate an
obstacle(Mortensen et al., 2007) ........................................................................................ 56 Figure 23 Obstacles around Jandakot airport mapped out in WAsP .............................. 57 Figure 24 A circle with 10km radius was divided in 12 equal sector with the
NSWTC testing pad at the centre overlaid on Google Earth image to identify the various roughness elements in each sector ..................................................................... 58
Figure 25 Roughness rose prepared for the NSWTC testing site based on Google Earth image ............................................................................................................................... 58
Figure 26 Screenshot of the predicted wind resource results by WAsP model for NSWTC testing facility ......................................................................................................... 59
Figure 27 WAsP predicted wind rose for NSWTC .............................................................. 60 Figure 28 Screenshot of the predicted wind resource results by WAsP model for
NSWTC testing facility using September to December 2009 wind data ............. 62 Figure 29 Predicted wind rose for NSWTC prepared for WAsP model validation .. 63 Figure 30 Graph comparing the wind speed frequency at 10magl, prepared with the
real measurements taken at NSWTC and WAsP predicted model ......................... 65
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Figure 31 Graph comparing the wind direction occurrences at 10magl, prepared with the real measurements taken at NSWTC and WAsP predicted model ................. 66
Figure 32 Monthly maximum and average wind speed recorded at Jandakot airport over 10 years ............................................................................................................................. 72
Figure 33 Graph prepared from the WAsP predicted monthly wind speed frequency results at 18magl at NSWTC test site ............................................................................... 73
Figure 34 Showing location of Cockburn Cement and NSWTC test facility ............ 113 Figure 35 Showing the missing data recorded at Cockburn cement ............................ 114 Figure 36 Showing location of Woodman Point and NSWTC test facility .............. 114 Figure 37 Showing location of Medina Research Centre and NSWTC test facility
.................................................................................................................................................... 115 Figure 38 Showing location of University of Melbourne weather station and
NSWTC test facility ............................................................................................................ 116 Figure 39 Showing location of Hope Valley Weather Station and NSWTC test
facility ...................................................................................................................................... 117 Figure 40 Showing location of Kwinana Industrial Council monitoring site at
Fancote Avenue and NSWTC test facility .................................................................. 118 Figure 41 Showing location of Jandakot Airport and NSWTC test facility ............. 119 Figure 42 Missing contours at the NSWTC test site represented by a turbine symbol
.................................................................................................................................................... 120 Figure 43 Roughness values suggested by the European Wind Atlas based on
characteristic of the terrain type (Petersen et al., 1989) .......................................... 132 Figure 44 Bench test results for the 2 cup anemometer P2546A and WAA151 ..... 134 Figure 45 Bench test results for temperature, relative humidity, barometric pressure
and wind direction sensor .................................................................................................. 135
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List of Tables Table 1 Table extracted from IEC61400-12-1 Annex B showing the test site
requirements(IEC, 2005, p. 36) .......................................................................................... 12 Table 2 Meteorological and electrical parameters required for power performance
testing .......................................................................................................................................... 13 Table 3 Showing the IEA proposed labelling and research parameters for power
performance test of SWTs .................................................................................................... 15 Table 4 Showing the wind speeds binned at 0.5m/s interval for the NSWTC testing
site wind data ............................................................................................................................ 23 Table 5 Showing the maximum slope of the site within different radius and checking
against IEC 61400-12-1 site criteria ................................................................................. 28 Table 6 Comparing various available meteorological monitoring instruments against
the IEC61400-12-1 and IEA proposed criteria ............................................................. 31 Table 7 Summarising monitoring instruments and their reason for purchase .............. 37 Table 8 Uncertainty associated with wind data observations over the corresponding
years (PEC590, 2008) ............................................................................................................ 46 Table 9 Showing % of missing data points in their corresponding year ........................ 49 Table 10 Showing the required parameters with their symbols to create an obstacle
list ................................................................................................................................................. 56 Table 11 Comparing the results of wind frequency distribution obtained from real
measurements and WAsP prediction at NSWTC ......................................................... 63 Table 12 Comparison of wind rose obtained from WAsP prediction and real
measurement ............................................................................................................................. 65 Table 13 Showing the predicted highest complete wind speed bins respective to their
heights of measurements ...................................................................................................... 69 Table 14 Showing the predicted range of wind turbines that can be tested at NSWTC
at 3 different heights .............................................................................................................. 70 Table 15 Specification of a 3kW Westwind Turbine ........................................................... 74 Table 16 Showing the predicted minutely database of wind resource at NSWTC test
site for individual months ..................................................................................................... 75 Table 17 Categories used in the formulation of the score card for assessing
sites(Whale, 2010) .................................................................................................................. 85 Table 18 Showing the tabular representation of wind rose measured at NSWTC
testing site ............................................................................................................................... 112 Table 19 Showing the WAsP predicted mean wind speed and their occurrence
frequency with respect to the directions ....................................................................... 120 Table 20 Showing the WAsP predicted wind speeds frequencies respective to their
bins determined by calculating the probability density function ......................... 121 Table 21 Showing the tabular representation of wind rose predicted at NSWTC test
site ............................................................................................................................................. 122 Table 22 Showing predicted wind speed bins at 12 mgal ............................................... 122 Table 23 Showing predicted wind speed bins at 18 mgal ............................................... 123 Table 24 Showing predicted wind speed bins at 24 mgal ............................................... 124
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Symbols and Units A Weibull scale factor °C Degrees Centigrade hPa Hectopascals Hz Hertz IEA International Energy Agency IEC International Electrotechnical Commission K Weibull shape factor Km kilometres kW Kilo Watts lm-2 liters per square meters Met Meteorological magl Meters above ground level m/s Meters per second Mbar Milli-bar NSWTC National Small Wind Test Centre RPM Revolution per minute V Wind velocity
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1 Introduction The dissertation focuses on assessing the requirements for power performance
testing at the National Small Wind Turbine Center test site, using the existing
standard (IEC1 and BWEA2) for small wind turbines (SWTs)3 as a tool.
1.1 Background Climate change is the most pressing issue we are facing today, which is putting the
human race at stake. One of the common suggestions to reduce potential greenhouse
gas emissions is to use renewable sources for energy generation. A rush can be seen
amongst governments as well as private sector to embrace green energy generating
technologies for example solar, wind etc. The use of renewables has picked up in last
2 decades and so has the small wind turbine market. Small wind turbines (SWTs)
have huge potential to harness electricity and for water pumping in remote as well as
urban areas. The global market of small-scale wind turbines is rapidly growing and
numerous start-up manufacturers have entered the market. The SWT market grew by
78% in the US in 2008 and similar trends have been seen in the UK (AWEA,
2009,p.3). Likewise, the number of SWT manufacturers globally have increased 3
fold in 2008 compared to 2006 (Whale & Brix, 2009). This indicates positive signs
for the SWT industry, but there is still significant baseline work required to ensure
consumer satisfaction and credibility of the industry. The following list gives brief
insight why SWTs industries have not been able to live up to its expectations-
• Despite there being over 300 SWT manufacturers around the world, only a
small number of SWTs (estimated to be between five and ten) are certified.
Currently there is no provision of non-accredited SWTs testing body.
1 International Electrotechnical Commission 2 British Wind Energy Agency 3 International Electrotechnical Commission has defined Small Wind Turbines with swept area less than 200 Sq. meters
2
Generally, the turbines are tested by an accredited testing body and then
certified by a certifying agent. Some of the testing bodies are also certifying
agents for example Germanischer Lloyd. To become an accredited testing
body takes considerable amount of time. Furthermore, the testing and
certification process is expensive. The growing SWTs industry demands a
cheaper, convenient and less time consuming process to test turbines. (Whale
& Brix, 2009)
• Given that there are various turbines available in the market, it becomes a
confusing task for customers to choose and compare the SWTs as no
common measure exists.
• The certification of wind turbines is expensive and is not within the financial
reach of the majority of SWTs manufacturers. Certifying SWTs at present
costs around US $200,000 -$250,00 (Whale & Brix, 2009). There are limited
numbers of certifying bodies around the globe. This makes them difficult to
access, as in many cases the turbines have to be transported overseas which
can result in a bottleneck for certification process. This also raises questions
as to the capacity of existing accredited testing bodies and certification agents
to meet with the large influx of start-up manufacturers entering the market.
• Due to the high cost for certification SWT companies with limited funds
introduce their turbine to the market with limited field-testing. Most of the
manufacturers have literally used their customers to test their products (Gipe,
1997). There have been instances where, SWT manufacturers were heavily
criticized for exploiting customers’ enthusiasm by making false claims such
as low start up speed, no noise etc (Gipe, 1997). This puts a serious question
on the credibility of the industry (Bergey, 2009).
These pressing issues have to be urgently addressed to ascertain the growth,
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development and credibility of SWTs industries. In 2008, International Electro-
technical Agency (IEA) started Task 27 - a campaign for small wind turbine
(SWT) labelling. “The intention was to set-up non-accredited SWT testing bodies
around the globe, testing against a common standard which has minimum
requirements for a testing process that will allow a standardised label to be
placed on products” (IEA, 2008). Seven countries around the globe are
committed to IEA Task 27, and are working mutually to develop recommended
practice for testing and labelling SWTs. The labels will relate the performance,
reliability, noise characteristics, and safety features of the turbines and it is also
believed that they will lessen the financial burden of the manufacturers for
testing with the use of non-accredited test facilities. The testing body can be a
university, 3rd party tester or manufacturer itself. The testing of turbines will then
provide feedback to manufacturers, which in turn will help in improving and
developing better products. Further the labels will make the buyers aware by
stating the performance and durability of the product under standard test
conditions. Hence it can be a stepping-stone for the manufactures to sell their
turbines, ensuring the reliability and performance of the system before actually
getting certified.
1.2 The National Small Wind Turbine Centre (NSWTC) The National Small Wind Turbine Centre (NSWTC) is a non-accredited testing body
and representative of Australia in the IEA Task 27 committee. NSWTC was
established in August 2008 and is funded by the Australian Government’s
Renewable Remote Power Generation Program (RRPGP). The test centre aims to
provide training, recommend testing practices, test and label turbines (1-5kW),
which will ultimately help in the development of the SWTs industry in Australia.
4
This facility will provide independent and affordable turbine performance testing,
durability test and noise measurements.
The IEA Task 27 committee has proposed a list of activities to develop the labelling
of SWTs. NSWTC is participating in most of the proposed activities, however at
present, special focus is given to the testing of SWTs, as it has to test at least 4
turbines to meet its milestone.
Currently the IEA recommended practices to test SWTs is under progress. However,
it has recently provided suggestions on instrument selection requirements for power
performance testing (Refer to in Section3.2.2). In absence of a documented
recommended practice from IEA, NSWTC committee has decided to follow the
IEC61400-12-1 standards for wind turbine testing. Nevertheless this dissertation will
also look at the BWEA wind turbine standards as to make comparisons against
IEC61400-12-1 standard in regards to the test site limitations in selection of turbine
type and it’s test duration for successful completion of a power performance test.
IEC standards are internationally acclaimed standards in the wind industries, while
BWEA standard is a national (UK) standard. IEC has produced a comprehensive list
of standard documents for testing wind turbines, which are -
• Power performance testing (IEC61400-12-1)
• Acoustics (IEC61400-11)
• Duration test (IEC61400-2) and
• Safety (IEC61400-2)
However, only one of the IEC standards is specifically for SWTs - IEC61400-12-2,
which relates to the design of the SWTs. The other relevant standards are written
with large wind turbines in mind, although some have made adaptations to try and
cover the case of SWTs. For instance IEC61400-12-1 has a section for SWTs
regarding procedures for carrying out power performance tests.
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1.3 Research Questions The aim of the dissertation can be seen in two sections –
• To assess the requirements for power performance testing, and
• To assess the limitations for power performance testing
The dissertation focuses on the test site and monitoring instrumentation and
their positioning in the requirement section. In the limitation section, the focus
is on long-term wind resource availability at the test site. To achieve this aim it
was realised that answers to the following research questions had to be sought
–
• What are the test site requirements for conducting power performance
testing?
• What sensors and monitoring devices are available for conducting the power
performance test?
• What is the cost for the sensors and monitoring devices?
• What resolutions are appropriate for the sensors and monitoring devices?
• What level of accuracy is required for the sensor and monitoring devices?
• What are the appropriate ways to arrange and mount the instruments for
power performance testing?
• What are the limitations of the NSWTC test site?
• What range of turbines can be tested at the NSWTC test site?
• What are the suitable times of the year to carry out the power performance
test for a given wind turbine?
1.4 Objective of the Project The dissertation aims to use the wind turbine-testing standard as a tool to achieve the
following objectives –
1st objective – Assessing the requirements for power performance testing
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• Checking test site compatibility with the IEC61400-12-1 standard
• Recommending brands of monitoring instruments by using the
IEC61400-12-1 standard and the IEA proposed selection criteria
• Recommending appropriate design for positioning of monitoring
instruments by using the IEC61400-12-1 standard as a tool
2nd objective – Assessing the test site limitations to identify factors that will assist to
manage the power performance test schedule at the test site such as-
• Types of turbines that can be tested, which meets the criteria set by
IEC61400-12-1 and the BWEA standard
• Suitable times of year for testing to satisfy the criteria set by
IEC61400-12-1 and the BWEA standard
• Overall length of time required to complete the test in accordance
with IEC61400-12-1 and the BWEA standard
1.5 Scope of the Project Power performance testing of wind turbines, involves a series of steps, from site
preparation, data collection and analysis to reporting. However, the dissertation only
focuses on the aforementioned objectives.
1.6 Overview of the methodology Literature review of the IEC61400-12-1, test site contour analysis, consultation with
experts is the main methodology followed in achieving the 1st objective. While Wind
Atlas modelling, literature review of IEC and BWEA standards and spreadsheet
analysis were carried out to achieve the second objective. A detailed methodology is
given in Chapter 2.
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1.7 Dissertation Structure The report consists of nine chapters. Chapter 2 focuses on the methodologies carried
out during the project. Chapter 3 refers to literature reviews on standards for power
performance testing. Chapter 4 provides background on the test site and discusses the
site requirements. Chapter 5 looks into the availability and selection of monitoring
instruments. Chapter 6 covers the process and results of wind modelling. Chapter 7
assess the test site limitations. Chapter 8 discusses the results, provides
recommendations and identifies future works. Finally conclusions are made in
chapters 9.
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2 Methodology This chapter discusses about the methodology followed in the report to achieve the
objectives of the project discussed in Section 1.4.
2.1 Methodology to First Objective The first objective is to assess the requirements for power performance testing. It has
two components to it- one is to check the site compatibility with the IEC61400-12-1
standard and the other to recommend brands and appropriate design for positioning
monitoring instruments. To achieve this objective the following methodologies were
carried out –
To check the NSWTC test site compatibility with the IEC61400-12-1 standard
• IEC61400-12-1 Annex B was reviewed to identify the necessary criteria
required to meet the standard.
• A detail analysis of the site’s topography was done using a contour map
prepared in Autocad by a surveyor company.
• The results from the site analysis were compared against the recommended
criteria in IEC61400-12-1.
• Finally after comparing the results, the necessary recommendations for site
requirements were made to NSWTC.
To recommend brands of monitoring instruments for the power performance testing
• IEC61400-12-1 standard was reviewed to identify the necessary criteria
required to meet the standard.
• The IEA proposed instrument selection criteria was reviewed
• Based on the criteria identified from both the above mentioned sources, along
with the experts consultation and web based information a instrument list was
prepared
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• Finally the instruments were recommended to NSWTC
To recommend appropriate design for mountings and arrangements of monitoring
instruments required for power performance testing
• IEC61400-12-1 Annex G was reviewed to identify the necessary criteria
required to meet the standard.
• The existing wind turbine and meteorological mast foundation on the test site
was reviewed
• Using the standard as a tool and keeping in mind the limitations of the
existing structural foundations on site, appropriate designs for the positioning
and arrangement of instruments were recommended
2.2 Methodology to Second Objective The second objective is to assess the test site limitations, which helps to identify the
factors that will assist to manage turbine-testing schedule. The limitations here
relates to the wind resource availability at the test site. To complete a power
performance test, the standards recommend a range of wind speeds, which are
derived from wind turbine power ratings. In general as the power rating of a turbine
increases, the required wind speed range for testing also increases. This imposes a
limitation on the size of a turbine that can be tested at the NSWTC test site, mainly
based on its wind resource availability. Hence it becomes essential to understand this
limitation. This understanding will provide assistance in managing turbine-testing
schedules by answering questions such as, when to test a turbine? How long would it
take to test? etc. The fundamentals for working towards the second objective are
based around the IEC 61400-12-1 standards. However, due to the Author’s personal
interest, a comparison of results (obtained under the 2nd objectives) based on the
IEC61400-12-1 and the BWEA standards was carried out.
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To achieve the above-mentioned objectives following methodologies were carried
out –
• The international power performance standard IEC61400-12-1, and the
BWEA standard were reviewed in order to assess the completion
requirements for testing
• Wind modelling was carried out using the wind atlas model, WAsP, in order
to predict the long-term wind resource at the site.
• Preliminary monitoring of the wind resource at the test site was used to
validate the model.
• The validated WAsP model was then used to prepare wind speed-binning
tables with 0.5m/s intervals at three different hub heights to identify the
limitations on the type of turbines that can be tested at the site in accordance
to the IEC and BWEA standards.
• Further, individual monthly wind speed-bins were predicted using the
validated model.
• These results were analysed by developing several spreadsheets and graphs to
identify the suitable months for testing and the time period required in order
to complete a power performance test for a given turbine.
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3 Literature Review The fundaments towards achieving the objectives laid out in this report are largely
built around the IEC wind turbine standards for power performance testing.
Nonetheless, the IEA proposed instrument selection and the BWEA standard were
also referred so as to address some of the objectives in the dissertation (Referred to
in section 2).
This chapter builds into the necessary background required to achieve the objectives
by providing insight on the recommendations suggested in the standards.
The reviewed literature required to achieve the corresponding objectives are stated
under the different headings in this chapter.
3.1 Literature Review for Assessing Site Requirements One of the essential criteria for performing a power performance test is that the
meteorological measurements taken at the mast must correlate well with the one
experienced at the turbine tower. To ensure this IEC 61400-12-1 Annex B
recommends site requirement criteria as listed in table 1 and figure 1.
Figure 1 Showing the areas to be assessed during site calibration in accordance to IEC 61400-12-1 Annex B (IEC, 2005, p. 36)
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Table 1 Table extracted from IEC61400-12-1 Annex B showing the test site requirements(IEC, 2005, p. 36)
As shown in figure 1, four sectors namely 2L, 4L, 8L and outside measurement
sectors have to be considered to check the test site compatibility, where ‘L’ is the
distance from the turbine tower to the meteorological mast and the outside
measurement sector is the area where the wind measurements get affected by the
wake of the turbine.
After identifying the different sectors on the site map, the maximum slope of the
plane that provides the best fit to the sectoral terrain (2L, 4L 8L) and passes through
the tower base should be identified. Likewise for the outside measurement sector, the
line of steepest slope that connects the tower base to the individual terrain points
within the sector should be identified. The determined slopes should then be
compared with the allowed maximum slope % in the corresponding sectors as shown
in table 1. If the target test site complies with the criteria provided in table 1, then no
site calibration is required and vice versa. Likewise if the target test site is within an
additional 50% of the maximum limits of the criteria, then a flow model can be used.
However, to validate the flow model, “the flow model shall show a difference in
wind speed between the anemometer position and the turbine hub less than at
10m/s for the measurement sectors” (IEC, 2005, p. 36)
3.2 Literature Review for Assessing Instrument Requirements The selection of monitoring instrumentation is important for carrying out the power
performance testing, as inappropriate instruments selection will lead to an invalid
13
test. This section will discuss on the instrumentation recommended by the IEC as
well as those proposed by the IEA.
3.2.1 IEC61400-12-1 Recommendations on Instruments The following table shows parameters required for power performance test
recommended by IEC61400-12-1.
Table 2 Meteorological and electrical parameters required for power performance testing
Parameters Units Meteorological Wind Speed m/s
Wind Direction Degrees Barometric Pressure Mbar Relative Air Humidity % Ambient Air Temperature °C
Electrical AC Output power of the inverter
kW
Equipments for measuring meteorological parameters
1. Wind Speed
Measurement of wind speed is the most important part of power performance testing.
IEC61400-12-1 recommends a calibrated cup anemometer for wind speed
measurements. It is also recommended that the cup anemometer should be calibrated
before and after the measurement and “the difference between the regression lines of
calibration and recalibration shall be within in the range of 6-12m/s”(IEC,
2005, p. 16). The selection of the anemometer depends on accuracy and terrain. If
the test site meets the IEC61400-12-1 site requirements (Refer to in section 3.1), a
cup anemometer with class type 1.74A5 is recommended (IEC, 2005, pp. 77-78).
4 “k” is a class number specified for selection of anemometer in accordance to site. 5 “A” is a class category if the site meets the IEC61400-12-1 Annex B criteria (section 4.1)
14
2. Wind Direction
Wind direction is measured with a wind vane. It is recommended, “The combined
calibration, operation and orientation uncertainty of the wind direction measurement
should be less than 5 degrees”. (IEC, 2005, p. 17)
3. Air Density
Air density is recommended to be derived using the following equation –
Where,
ρ = air density
T = air temperature
Ro = Gas constant of dry air
B = air pressure
According the IEC61400-12-1 standard Annex E, air temperature sensor and
barometric pressure sensor should have an accuracy range of °C and hPa
(IEC, 2005, pp. 50-51).
4. Power Measurements
The class of transducers for measuring power and current has to comply with the
IEC 60044, which is required to be class 0.5 or better. Further it should be able to
measure within a range of -50 to 200% of turbine rated power. (IEC, 2005, p. 16)
6. Data Acquisition System
IEC61400-12-1 recommends a data acquisition system with a sampling rate greater
than a 1Hz. It also recommends verifying the signals at the transducer ends by
comparing it to the recorded readings. “As a guideline, the uncertainty of the data
15
acquisition system should be negligible compared with the uncertainty of the
sensors”.(IEC, 2005, p. 18)
3.2.2 Parameters for Turbine Power Performance Testing Proposed by IEA Task 27 NSWTC is one of the participants in the IEA Task 27 trial for turbine labelling and is
to carryout power performance testing at its site in accordance to the IEC61400-12-1
standard (Referred to in Section 1.2). The significance of mentioning the IEA
proposed instrumentation in this dissertation is to identify whether the same set of
equipment is able to satisfy both the IEC61400-12-1 and the IEA instrument
requirements. This prevents the hassle of re-purchasing different sets of instruments,
if in future NSWTC has to test in accordance to IEA recommended practices.
In December 2009, the IEA wind Task 27 proposed the following parameters for
labelling and research purposes to conduct power performance testing of small wind
turbines –
Table 3 Showing the IEA proposed labelling and research parameters for power performance test of SWTs
Parameters Units Type Range Accuracy Meteorological
Wind Speed m/s L 0-65 m/s (from 0-25m/s)
Wind Direction Degrees L 0-360 Barometric Pressure Mbar L 600-
1100 0.1hPa
Relative Air Humidity % L 5-98 Ambient Air Temperature
°C L -30 - 50
Precipitation l.m-2 R 0-200 Mechanical Rotational Speed rpm R 0-1000
Yaw Direction Degrees R 0-360 Electrical Output Voltage (input of
the rectifier, AC) V R 0-Voc Class 0.5
Output Power (input of the rectifier, AC)
kW R 0-2PN Class 0.5
Electric Frequency (Input of the rectifier, AC)
Hz R 0-100 Class 0.5
DC Output voltage of the wind controller
V R 0-Vmax
Class 0.5
16
DC Output current of the wind controller
A R 0-Imax Class 0.5
AC Output power of the inverter
kW L 0-2PN Class 0.5
*L= Labelling Parameters, R = Research Parameters, PN = Nominal
3.3 Literature Review for Mounting and Arrangements of Monitoring Instruments Arranging and mounting of monitoring instruments are as equally important as the
other sections previously discussed in this chapter. Appropriate positioning of the
instruments ensures that their readings are not affected by any obstacle or wake of
the turbine. To ensure this the IEC61400-12-1 standard recommends the following -
1. Location of Meteorological Mast
In the case of horizontal wind turbines, the meteorological mast should be at a
distance between 2 to 4 times the rotor diameter “D” from the turbine. It is
recommended to position the mast upwind of the turbine in the prevailing wind
direction.(IEC, 2005, pp. 14-15)
Pertinent to the testing of SWTs is clause G in Annex H which, states that a separate
meteorological mast is not required for testing SWTs as long as a minimum distance
of 3 meters from the turbine rotor to the instruments (anemometer, vanes etc.) is
maintained. (IEC, 2005, p. 74)
2. Measurement Sector
Measurement in the directions with considerable obstacles and turbine wake effects
should be excluded. Figure 2 shows the sectors that should be excluded due to the
wake of the turbine. The disturbed sectors can be approximated at 81°, 74° and 59°
for 2D, 2.5D and 4D respectively.
17
Figure 2 Showing the measurement sectors that has to be excluded during analysis of data (IEC, 2005, p. 15)
3. Arrangements of Monitoring Instruments on Meteorological Mast
Figure 3 Extracted from IEC61400-12-1 showing the arrangement of monitoring instruments on a boom(IEC, 2005, p. 69)
18
The mounting of instruments has to be carried out carefully as flow distortion due to
the meteorological mast can significantly affect the measurements. Instruments can
be mounted on a tubular or a lattice mast with or without a boom. In this section,
arrangement of instruments is focused on a tubular self-standing mast with boom
mountings.
As shown in figure 3, according to IEC61400-12-1 Annex G, on a tubular
meteorological mast the cup anemometer has to be mounted at a vertical distance of
at least 15 times the boom diameter to keep the flow distortion (due to the boom)
below 0.5%. The instrument-supporting boom should be extended away from the
mast at a distance of 6-8 times the mast diameter to minimise the flow distortion to
less than 1% - 0.5% respectively. Further, the anemometer has to be within
of the hub height of the turbine. (IEC, 2005, pp. 67-69)
The primary and a secondary cup anemometer have to be separated at least 1.5 to a
maximum of 2.5m away from each other (Referred to in Figure 3). Whereas the
other instruments, like the wind vane, temperature sensors etc., should be mounted
within 10% of the hub height.
3.4 Literature Review Assessing the Test Site Limitations As discussed in section 2.2, one of the limitation factors while conducting a power
performance test is the availability of wind resource on the site. Hence it becomes
essential to understand this limitation at the target site (NSWTC). This understanding
will provide assistance in managing the turbine-testing schedules and answering the
following questions: what type of turbine to test? When to test a turbine? How long
would it take to test? etc.
Before starting to seek answers to these questions, it is essential to understand the
recommendations suggested by the standards. The standards recommends the
19
required criteria necessary in preparation of the measured data to complete a power
performance test, such as - frequency of sampling data, the range of wind speed
required for testing a given turbine, wind speed binning, number and hours of data
points essential to complete the test etc. This section discusses about these
recommendations suggested in the IEC61400-12-1 standard and BWEA standard. As
mentioned earlier in section 2.2, the reason behind introducing the BWEA standard
in this dissertation is out of Author’s personal interest, to see how the results differ
between each of the standards.
The recommendations suggested by IEC61400-12-1 are as following – Data Sampling and Wind Speed Binning in Accordance to IEC61400-12-1 According to IEC61400-12-1, the data has to be sampled at 1Hz or greater. The
sampled data should be recorded at 1minute averages for further analysis. (IEC,
2005, p. 18)
The data set for binning wind speed is said to be complete given the following
criteria is satisfied-
• “Each wind speed bins between 1m/s below cut-in-and 14m/s shall contain a
minimum of 10 minutes of sampled data”
• “The total database contains at least 60 hours of data with the small wind
turbine within the wind speed range”
(IEC,2005, p. 71)
The completed data set as mentioned above should cover the following criteria for a
complete power performance test -
• “Wind speed range extending from 1m/s below cut-in speed to 1.5 times the
wind speed at 85% of the rated power of the wind turbine”(IEC, 2005, p. 19)
• The wind speed bins have to be at intervals of 0.5m/s and the mid of bin
ranges have to be multiples of 0.5m/s (IEC, 2005, p. 19)
20
Data Sampling and Wind Speed Binning in Accordance to BWEA Standard
The BWEA standard is the national standard for small wind turbines in UK. This is
largely based on IEC61400-12-1 standards. However there are slight differences
introduced to relax the standards as the IEC61400-12-1 is written with large wind
turbines in mind with some adaptations to try and cover the case of SWTs. The only
difference in data sampling and wind speed binning in the BWEA standards are as
follows –
• “ The database shall include 10 minutes of data for all wind speeds at least
5m/s beyond the lowest wind speed at which power is within 95% of
maximum power (or when sustained output is attained)” (BWEA, 2008, p. 7)
21
4. NSWTC Test Facility According to the NSWTC Director 18 potential sites were initially identified for
establishing the test facility (Whale, 2010). The sites were scored against 6 criteria
(Refer to Appendix A1) and 5 sites were shortlisted. The top ranked site however
was not selected as planned future construction could potentially obstruct the
available wind resource. Thus it was decided to focus on another of the shortlisted
sites - the Henderson Waste Recovery Park (HWRP) The HWRP is located at 32°10'
0.41"S longitude and 115°47'54. 14"E latitude and is 24km aerial distance South-
West from Perth city, Western Australia. The site is within accessible distance for
frequent visits.
Figure 4 Showing the location of NSWTC test site (Courtesy: Google Earth)
4.1 Installation of Preliminary Wind Monitoring System In September 2009, a 10m met-mast was installed at site to do preliminary wind
measurements, the author was involved in the installation of the mast. Special care
had to be taken during the installation of the guy wire anchors as the site is a landfill
and penetration deeper than 60 cm could cause damage to the geo-textile membrane
22
sheltering the methane gas underneath. A wind speed measuring cup and a direction
measuring vane from Davis Instruments were installed on the mast, their
specifications are provided in Appendix B1. The sensor was setup to record every
minute and data was transferred via a wireless communication port.
Anchors laid to the ground
Mast anchors cemented to the ground to
provide stability
10 meter met-mast at the NSWTC test
site
The wind speed and direction sensor
23
Wireless communication for data transfer recorded by the wind sensors
Figure 5 Series of snap shots taken during the installation of the preliminary monitoring system and the mast (Courtesy: NSWTC)
4.1.1 Data from Preliminary Wind Monitoring Four months (September, 09 to December, 09) of 1-minute averaged data was
available from the preliminary wind monitoring system measured at 10 m a.g.l6 at
the NSWTC test site. As shown in table 4, to analyse the wind resource availability
at the site, the minutely data was averaged to 10 minutes and binned at an interval of
0.5m/s. Further, a wind rose was prepared to identify the distribution of wind
directions in 12 equal sectors within 360 degrees (Refer to Figure 6).
Table 4 Showing the wind speeds binned at 0.5m/s interval for the NSWTC testing site wind data
Bin No. Bin Min
(m/s) Bin Max
(m/s) Bin Mid
(m/s)
Wind Speed
Frequency 1 0.25 0.75 0.5 311 2 0.75 1.25 1 423 3 1.25 1.75 1.5 671 4 1.75 2.25 2 874 5 2.25 2.75 2.5 1124 6 2.75 3.25 3 1135 7 3.25 3.75 3.5 1265 8 3.75 4.25 4 1265 9 4.25 4.75 4.5 1317
10 4.75 5.25 5 1312 6 Meters above ground level
24
11 5.25 5.75 5.5 1240 12 5.75 6.25 6 1019 13 6.25 6.75 6.5 877 14 6.75 7.25 7 718 15 7.25 7.75 7.5 643 16 7.75 8.25 8 462 17 8.25 8.75 8.5 393 18 8.75 9.25 9 278 19 9.25 9.75 9.5 213 20 9.75 10.25 10 153 21 10.25 10.75 10.5 87 22 10.75 11.25 11 66 23 11.25 11.75 11.5 63 24 11.75 12.25 12 32 25 12.25 12.75 12.5 27 26 12.75 13.25 13 12 27 13.25 13.75 13.5 5 28 13.75 14.25 14 6 29 14.25 14.75 14.5 4 30 14.75 15.25 15 2 31 15.25 15.75 15.5 2 32 15.75 16.25 16 1
Table 4 shows the binned wind speed and their corresponding frequency of
occurrences. The average wind speed was found to be 4.83m/s at 10 magl during the
4-month period of measurement.
Figure 6 Wind rose diagram prepared from the preliminary measurements recorded at NSWTC
25
Figure 6 shows the wind rose diagram created from the data measured at NSWTC
testing facility. The figure shows that the most prevailing wind direction is Easterlies
and South-Westerlies. The wind direction frequency in a tabular format is presented
in Appendix C1.
4.2 Installation of Wind Turbine Tower and Meteorological Mast In February 2009, the author was involved in installing, an 18 meters wind turbine
tower and a meteorological mast of same height at the NSWTC test site. The centre
of the meteorological mast was positioned at a fixed distance of 7 meters from the
turbine tower base. They were positioned in the flattest possible location within the
NSWTC testing facility to minimise the flow distortion due to the sloping of the
terrain.
26
Figure 7 Series of snap shots taken during the installation of the preliminary monitoring system and the mast (Courtesy: NSWTC)
4.3 NSWTC Test Site Requirements A surveying team was hired to survey the NSWTC test site and prepare a site
contour map (Refer to Appendix A2). The Author used this map to determine the
maximum slope variations in 4 different sectors as mentioned in section 3.1. The
following procedures were carried out in doing so –
As shown in figure 1 in section 3.1 four radial sectors namely 2L, 4L, 8L (where “L”
is the distance from the met-mast to the turbine tower) were drawn on the site map.
Each sector plane under consideration such as, =>2L< 4L, 2L etc. (Refer to Table 1)
was thoroughly examined to identify the maximum slope of the plane that provide
the best fit to the sectoral terrain (2L, 4L 8L) and passed through the turbine tower
base.
An example calculation is shown below –
27
Figure 8 shows an enlarged view of a section on the site map. It shows the height
difference and distance between the maximum and minimum contour lines
representing the boundaries of the sector plane between 2L and 4L.
Figure 8 Shows an enlarged section on the NSWTC site map
Mathematically the maximum slope % is given by
Maximum Slope% = Tan-1 (Max. Rise/Max. Run) X 100 %
= Tan-1 (1.93/19.4) X100% (Refer to in figure 8)
= 9.9 % is maximum slope percentage in sector =>2L < 4L
Where,
Max. Rise =Height difference between the maximum and minimum contour lines
within the sector
Max. Run = Distance between the maximum and minimum contour lines
28
Similar steps were carried out to determine the maximum slope percentage in the
other remaining sectors. Table 5 was prepared to summarise the results and compare
them with the criteria recommended by IEC61400-12-1 (Refer to Table 1).
Table 5 Showing the maximum slope of the site within different radius and checking against IEC 61400-12-1 site criteria
Distance Sector Maximum Slope % in
the given sector
Meets IEC
criteria
2L 360˚ 8 NO
=>2L and <4L Measurement
sector
9.9 NO
=>2L and <4L Outside
Measurement
sector
4 YES
=>4L and <8L Measurement
sector
17 NO
From the analysis it was found that the NSWTC testing site had a steeper slope
towards the Eastern side. According to the Wind Test Engineer at NSWTC a site
calibration may not be required if a sector of 50 degrees towards this direction is
discounted. However the Author suggests that discounting such a large sector
(approximately 17.3%) might have significant impact in completing the required
wind speed range during power performance testing of turbines (Refer to Section
3.4) given that one of the prevailing winds are easterlies (Referred to in Figure 6).
29
From Table 5, it can be concluded that the NSWTC site does not meet the
IEC61400-12-1 Annex B criteria as the maximum allowed slope exceeds the defined
limits. Hence the Author recommends NSWTC to carry out a site calibration in
accordance to the IEC61400-12-1 standard.
30
5 Monitoring Instruments for Power Performance Testing This section identifies and recommends the available instruments to perform a power
performance test. There are a wide variety of instruments available in the market for
the respective parameters under consideration in this report, so it is not practical to
discuss each of them. However, a shortlist of equipment was prepared based on
• Criteria to satisfy IEC61400-12-1 (Referred to in Section 3.2.1) and proposed
recommendations by IEA (Referred to in Section 3.2.2)
• Consultation with experts in monitoring instruments at RISE7 and CSIRO8
• Highly recognised and commonly used instruments in this field,
• Cost
• Instruments previously purchased by NSWTC
5.1 Instruments for Meteorological Parameters Based on these 5 parameters, a table listing instruments for meteorological
parameters was prepared in order to compare them against each other and the
standard. The details of each instruments presented in table 6 is available in
Appendix B.
7 Research Institute for Sustainable Energy 8 Commonwealth Scientific and Research Organisation
31
Table 6 Comparing various available meteorological monitoring instruments against the IEC61400-12-1 and IEA proposed criteria
Instrument Manufacturer
Model No.
Range Accuracy Output Signal
Supply Calibration Meets IEA Proposed Criteria
Meets IEC Criteria
Cost Remarks
Cup Anemometer
NRG NRG#40 0-96 m/s
0.1m/s within range of 5-25m/s
1Hz per m/s
5-24VDC MEASNET /IEC61400-12-1
YES NO $427 Measures only horizontal wind speed, Class Type NA*
Vector A100M 0-75m/s
1% within range of 10-55m/s
10Hz per 1m/s
4.5-28VDC
MEASNET /IEC61400-12-1
YES YES $710 +$410(calibration)
1.8A Class Type, 1st class anemometer considered by the IEC and MEASNET standard
Vaisala WAA151 0-75m/s
0.17m/s with range of 0.4-55m/s
10Hz per 1m/s
9.5-15.5VDC
ASTM D5096-90
YES NO $1000 Class Type NA
RISO P2546A 0-70m/s
0.03m/s within 4.5-16m/s
1Hz per m/s
<30VDC MEASNET /IEC61400-12-1
YES NO $2250 1.31A Class Type
Wind Vane NRG NRG#20
0 0-360 ° 1% DC
Voltage 1-12VDC YES YES $221 Dead-band near
North ranging from a maximum
32
of 8˚ to a more typical value of 4˚.
Vector W200P 0-360 ° 3° in steady wind over 5m/s
DC Voltage
1-5VDC YES YES $828 Within 2° obtainable with calibration
Vaisala WAV151 0-360 ° Better than 3° 6 Parallel GRAY Code
9.5-15.5VDC
YES YES $1080
Temperature /Humidity
Vaisala HMP155 RH =0-100% , Temp = -80 - 60°C
RH = 0 to 90%: 1%, 90-100%: (0.226-0.0028x
temperature): -80 to +20°C,
(0.055+0.0057x temperature) 20-60°C
0-2.5VDC
7-28VDC YES YES $320
RM Young 41382 RH =0-100%, Temp = -50 - 50°C
2% at 20°C, 0.3°C at 0°C
0-1VDC
10-28VDC
NIST traceable
YES YES $834 Accuracy up to 0.1°C at 0°C
available
Pressure Sensor
33
NRG BP20 15-115kPa
1.5kPa (0.15hPa)
DC Voltage
7-35VDC NIST traceable
NO YES $325
RM Young 61302V 50-110kPa
0.05% 0-5VDC
7-30VDC YES YES $650
Onset S-BPB-CM50
66 -107kPa
0.5kPa over a range from -40˚ - 70˚C (0.05hPa)
NA NA YES YES $269 Needs a RJ45 compatible logger
*NA Not Available
** Prices are in Australian Dollars
34
5.2 Recommendations on Meteorological Measuring Instrument The following lists out the recommended instruments for measuring meteorological
parameters required in power performance testing -
• Vector Instruments VA100LM cup anemometer is recommended as it
satisfies the IEC61400-12-1 and IEA standard. It has local support and
accessibility to spare parts locally (Refer to Appendix B2). P2546A and
Vaisala WAA151 are also highly accurate instruments but don’t meet the
IEC61400-12-1 class type criteria, nevertheless it does meet the IEA
proposed criteria.
• All the vanes comply with the IEC61400-12-1 and the IEA criteria. The NRG
wind vane is recommended as it is the cheapest option amongst the three;
however, it has the largest range of dead band with typical value of 4° near to
North9, while compared to the other vanes discussed (Refer to Appendix B3).
• Use of integrated humidity and temperature sensors reduces the sensor wiring
length and occupies only a single channel in a data logger compared to using
two different sensors. It was realized that there are limited integrated
temperature and humidity sensors available in the market. Vaisala HMP155 It
is recommended as it is relatively more accurate then the R.M Young 41382
sensor and meets IEC61400-12-1 and the IEA criteria (Refer to Appendix
B4).
• The onset S-BPS-CM50 pressure sensor is the most accurate and cheaper
option compared to R.M. Young and NRG sensors. However, the
communication port is via a RJ45, which needs a special logger to read the
measurements. Further, an additional logger will increase the cost. The other
option that satisfies the IEC61400-12-1 and the IEA criteria is the R.M.
9 In the dead band zone no measurements are sampled by the vane
35
Young 61302V. The NRG BP-20, although cheaper, misses the IEA
proposed requirement by +-0.05hPa, but is valid to the IEC61400-12-1
standard (Refer to Appendix B5).
5.3 Instrument for Electric Parameter Power Transducers Power transducers are used to measure the AC power at the inverter output.
Transducers with Class 0.5 or better and measurement range from -50% – 200% of
turbine power rating is recommended by IEC61400-12-1 for power performance
measurement of the wind turbines. As NSWTC plans to test turbines up to 5kW, the
power transducer ratings will largely vary respective to the turbines ratings. A single
10kW transducer for testing turbines from 1-5kW is not a recommended practice as
the resolution is largely decreased for relatively smaller turbines. This will create
uncertainty in measurements and hence the transducer may no longer meet the
required standards. It is therefore recommended that transducers that meet the IEC
standards but with appropriate resolutions. Analogy Process Control System is one of
the reputed transducer manufacturers in Australia and provides a wide range of
power transducers (A.P.C.S, 2010).
Figure 9 AWT190 power transducer with class of 0.2 (Courtesy NSWTC)
36
5.4 Instrument for Data Acquisition Data Loggers There are a variety of data loggers available in the market such as Campbell
scientific loggers, Datataker loggers etc. However due to the familiarity and past
experiences of the NSWTC staff with Datataker Loggers, it was recommended.
Datataker is one of the well-known data logging systems available and DT80 is one
of their latest products, which was released in 2007/08. It has 15 analogue channels
and 10 digital channels. It has a sampling - rate up to 25Hz and accuracy is within
0.1% for a temperature range of 5-40°C (Datataker, 2010). It complies with the
IEC61400-12-1 standards discussed in section 3.2.1.
Figure 10 Picture of DT80
37
5.5 Bench Testing NSWTC had previously purchased a set of equipments to perform the power
performance test before the outcome of this report. Table 7 below shows the list of
the equipments and the reasons they were purchased as provided by the Technical
Manager at NSWTC.
Table 7 Summarising monitoring instruments and their reason for purchase
Sensor Type Model Reason for Purchase
Cup Anemometer Vaisala WAA151 On the basis of
recommendations made by
CSIRO and previous
experience
P2546A On the basis of
recommendations made by
CSIRO
Wind Vane NRG#200 Based on cost price
compared to other wind
vanes in the market.
Widely used by other
testing agencies.
Furthermore, wind vanes
are easily calibrated and
often cheaper than cup
calibration.
Temperature/Humidity HMP50 Based on cost and past
experience
Barometric Sensor NRG BP-20 Cheaper option and
38
previous experience
The author carried out a bench test of the NSWTC purchased equipment, with the
assistance of the Technical Manager at NSWTC to test the data logger programming
and check the sensor readings.
Figure 11 Bench testing setup of the monitoring equipments
Figure 11 shows the setup for bench testing of the monitoring equipments.
Procedures
DT80 was used as the data acquisition hardware. A program was written in Delogger
Pro 5 software to sample and record the sensor measurements in the DT80 at every
1-second (Refer to Appendix E1). A flow diagram in figure 12 shows the
connections of the sensors, power supply and PC communication to the DT80. A fan
was set at constant speed and was faced towards the cup anemometers to record the
variations in the readings of the two-cup anemometers.
It was concluded that the sensors were providing realistic measurements. The
recorded measurements of the sensor during the bench test can be visualised in the
graph in Appendix E2.
39
Figure 12 Flow diagram of sensor connection to the data-logging unit
Datataker DT80
Wind Vane
Secondary Cup Anemometer
Primary Cup Anemometer
12VDCPower Supply to DT80
Barometric Pressure Sensor
Temperature/Humidity Sensor
PC to communicate with DT80
40
5.6 Arrangement and Mounting of the Monitoring Instruments According, to the IEC61400-12-1 standard (Referred to in Section 3.3) for SWT
power performance testing the meteorological mast has to be positioned 2 to 4 times
the rotor diameter from the turbine tower or at a distance of 3 meters away from the
rotor. An inquiry to the Secretary of the IEC confirmed that 2 to 4 times the rotor
diameter still applies for the latter, even though this is not clearly stated in the
standard.
Furthermore, it makes no sense to take a relative distance from the meteorological
mast to the turbine tower, unless the centreline of the anemometer and the mast are at
the same distance from the tower. Hence it is assumed that, when standards refer to
the position of the mast, it is actually the centre-to-centre distance between the
anemometer and the turbine tower.
At present, the meteorological mast at the NSWTC test site is positioned upwind of
the turbine in the prevailing wind direction at a distance of 7 meters away from it
(Referred to in Section 4.2). With the present mast set-up at NSWTC the maximum
possible rotor diameter that can be tested is limited to 3.5meters (2 times the rotor
diameter, 7/2 =3.5m) (Referred to in Section 3.3). However, the test centre aims to
test turbines up to 5 meters in rotor diameter. This means that the distance between
the turbine tower and the meteorological mast (with the anemometer positioned at
the centreline of the mast) should be at least 10 meters to meet the IEC61400-12-1
standard. The Author discusses two design options to achieve this objective –
1) The position of the met-mast should be relocated to 10 meters relative to the
turbine tower, upwind of the turbine in the prevailing wind direction. For this
a new concrete foundation should be laid out. According to the NSWTC
Manager laying out a new foundation will cost approximately $1000. Further,
the reinstallation of the mast and the decommission cost will also add up. The
time period for turbine testing will also be increased.
41
2) The second option is to arrange the instruments on a boom mounting as
shown in figure 13 and 14, positioned upwind of the turbine in the prevailing
wind direction. The arrangement shown in the figures meets the IEC61400-
12-1 standards mentioned in section 3.3 (Referred to in Figure 3).
Figure 13 Top view of the recommended instrument mounting arrangement
According to the IEC61400-12-1 standard the distance of the boom from the
meteorological mast has to be at least 8 times the met mast diameter to minimize the
flow distortion to 0.5%. This distance recommended in the case of NSWTC is at
least 3 meters. Extending the arm length to 3 meters along with appropriate structural
support, will allow the anemometers to be placed at a distance of 10 meters away
from turbine tower and hence will satisfy the standard to measure up to 5 meters
rotor diameter.
Turbine Tower
Met-Mast
Primary Anemometer
Boom
Secondary Anemometer
Arm (Length 8 times the mast) diameter
7 meters
42
Figure 14 Side view of boom mounting with recommended distances from instrument arrangements to meet the IEC61400-12-1 standard
This arrangement will allow NSWTC to test wind turbines up to 5m-rotor diameter
without major modification and high cost. The arrangement assembly can be quickly
changed according to need and hence will also save significant time and cost relative
to the first option.
Minimum1.5m maximum 2.5m
Minimum 0.75m
Minimum 25 times boom diameter
Wind Vane, temperature probe etc.
Min 1.5m & max. 10% of the hub height
43
6. Predicting Wind Resource at NSWTC Using WAsP Modelling The preliminary measurements at the site as mention in section 4.1.1 were not
enough to conclude whether the wind resource availability at the site was enough to
complete the wind bins for a given turbine to comply with the IEC61400-12-1 and
BWEA standard (Referred to in Section 3.4). Clearly a need for longer-term
prediction of wind data at the test site was required. Hence to achieve this objective,
Wind Atlas modelling through the WAsP software was carried out.
WAsP is a PC program developed by Wind Energy Division at Risø DTU, Denmark
for predicting wind climates, wind resources and power productions from wind
turbines and wind farms (WAsP, 2010). “The predictions are based on wind data
measured at stations with the same regional climate as the target site. The program
includes a complex terrain flow model, a roughness change model and a model for
sheltering obstacles”. (WAsP, 2010)
The flow diagram extracted from the European Wind Atlas provides an overview on
WAsP methodology-
44
Figure 15 showing WAsP methodology (Petersen et. al.,1989, p.17)
• As shown in figure 15, wind data is taken from a meteorological station
(which is the reference site) and is then modelled for sheltering obstacles
around it.
• In the next step, a roughness model for the terrain is prepared.
45
• The meteorological site is then identified on a contour map.
• By following the above 3 steps a Wind Atlas (site independent climate) is
produced by taking observed wind data and then cleaning it for the site-
specific obstacles, roughness and terrain.
• After the preparing the Wind Atlas, the target site is located on the same
contour map.
• Specific obstacles, roughness and terrain of the target site are added to the
Wind Atlas and predictions are made.
This chapter discusses –
• The preliminary preparations for a WAsP model,
• Procedures to create the model,
• Results obtained from the model,
• Analysis of the obtained results and
• Validation for the WAsP model
6.1. Considerations for Selection of a Reference Site To create a WAsP model, selection of an appropriate reference site is very important.
This section discusses the parameters to consider while selecting a site for WAsP
modelling.
6.1.1. Length of Data Available Longer periods of data give better predictions of wind resource, but the “Law of
Diminishing Returns” applies if the amount of data keeps increasing. Ten years of
data is needed before estimates are accepted, though in common practice 1-2 years of
data on site is correlated with nearby met stations (Whale, 2008). Table 8 shows
uncertainty associated with the wind data observations over the corresponding year.
46
Table 8 Uncertainty associated with wind data observations over the corresponding years (PEC590, 2008)
Number of Observations (Years)
Uncertainty of estimate (±)
1 35%
2 25%
4 18%
8 12%
16 9%
50 5%
6.1.2 Nearest to Similar Terrains Wind is highly affected by terrain. Wind speed differs depending on what surface it
is blowing over, due to the variation of friction so exerted by it (Petersen et al., 1989,
pp. 15-23). Water surface will not retard wind speed as rough surfaces such as
bushland. Although WAsP accounts for variations in terrains a similar site selection
will reduce error in the model.
6.1.3 Least Obstructed Site Reference sites (meteorological stations) are normally installed in open areas with
minimum obstacles, though this may not always be the case. Objects around the
station are treated as obstacles if the anemometer is “closer than about 50 obstacle
heights to the obstacle and closer than about three obstacle heights to the ground”
(Mortensen et al., 2007). “If the point of interest is further away than about 50
obstacle heights or higher than about three obstacle heights, the object should most
likely be included in the roughness description” (Mortensen et al., 2007).
6.1.4 Data Quality Very few sites have a complete unbroken record of climate information. There can
be gaps due to several reasons such as instrument malfunction, power loss and error
47
in memory cards etc. For better estimates met sites with good quality data should be
selected.
6.2 Identification and Selection of Reference Site
Figure 16 Showing location of NSWTC test facility along with the three short listed sites (Courtesy – Google Earth)
Seven potential reference met-station sites located close to the NSWTC testing
facility were investigated. The details of each site can be found in Appendix D1.
After closely examining all the potential reference sites, based on the criteria listed in
section 6.1, three potential sites (Refer to Figure 16) were selected namely -
• Department of Environment and Conservation Hope Valley Weather Station
(HVWS)
• Kiwnana Industrial Council Fancote Avenue (KIC)
• Jandakot Airport
Among these 3 sites Jandakot airport was selected because of the following reasons-
• Offers large data set - half hourly data since 1994 to January 2010
48
• WAsP recommends use of half or hourly data for analysis (Bowen &
Mortensen, 1996)
• Periodic maintenance is carried out by Bureau of Meteorology ensuring the
integrity and reliability of data measured
• Previous work carried out during student projects suggests that data obtained
from KIC and HVWS were of low quality (Lee, 2008)
The NSWTC test site has the Indian Ocean to its West at an approximate aerial
distance of 3km, whereas Jandakot airport is in-land (Refer to figure 16). However as
WAsP models water surface, this may not affect the prediction. It was concluded that
climate data from Jandakot airport was the most appropriate for WAsP modelling.
6.3 Data Handling This section discusses screening and verification of the Jandakot data. Half hourly
data at 10magl since 1994 to January 2010 for Jandakot Airport was received from
the Bureau of Meteorology. Out of 16 years of available data, the last 10 years was
taken into consideration for the WAsP analysis10. Since no weather station has
completely unbroken data, data verification is essential before proceeding to any
kind of analysis. As stated in the NREL “Wind Resource Assessment Handbook”
there are two parts to data validation -
• Data Screening
This involves screening unusual values present in the recordings. The suspected
values may or may not be erroneous for example unusual average wind speed may be
recorded during a storm (Bailey & McDonald, 1997). There were random recordings
present in the Jandakot data. It was advised by the Bureau of Meteorology, that
10 Table 8 shows that data observation over eight year has uncertainty of 12% whereas 16 year is 9%, it is assumed that the difference in uncertainty between 10 years and 16 years is not very large.
49
significant change in wind speed, wind direction, temperature etc. had to be recorded
for aircraft safety purposes. Hence there were random interval recordings in the data.
A logical statement (column “M”) in MS- Excel was created to filter out the values
that were not half hourly recordings.
Figure 17 Column 'F' showing recordings at other than 30 minutes interval, such data were filtered out
In Figure 17, column “F” (showing minutes) has data points recorded at intervals
other then 30 minutes. These values were deleted from the data set. After filtering the
data, the missing values in half hourly intervals were left blank because interpolating
wind speed and direction is not considered appropriate and might give false results.
Table 9 Showing % of missing data points in their corresponding year
Year Missing Data Points Total Data Points % Of Data Gaps
1999 933 17520 5.3
2000 998 17568 5.7
2001 1730 17520 9.9
2002 1158 17520 6.6
2003 1463 17520 8.4
2004 1183 17568 6.7
2005 1356 17520 7.7
2006 1247 17520 7.1
2007 1150 17520 6.6
50
2008 1326 17568 7.5
2009 1225 17520 7.0
Table 9 shows the missing data points for the corresponding years. Each year has
17520 or 17568 (leap year) data points. The percentage of missing data events are
below 10% and ranges from a minimum of 5.3% in year 1999 to a maximum of 9.9%
in 2001. On an average, 7.1% data was found to be missing over the 10 year period;
this can be considered as a good data set.
• Data Verification
According to the NREL, data verification “requires a case-by-case decision on what
to do with the suspect values, retain them as valid, reject them as invalid, or replace
them with redundant, valid values (if available)” (Bailey & McDonald, 1997). A
logical statement was created in MS-Excel to isolate high range values. No such
unusual values were identified during the data screening process. This result was
cross examined using “WAsP Climate Analyst 9.0”. The Climate Analyst is a utility
software within WAsP and provides a summary report of the data fed into the
system, it reports the minimum, maximum and out of range values.
6.4 WAsP Modelling
The wind data measured at Jandakot airport should be different to the data measured
at the NSWTC testing facility because of the difference in terrain, surrounding
obstacles, properties of the meteorological station (example- height of the
anemometer). By using WAsP 9.0, the data measured at Jandakot Airport can be
used to predict the wind resource at the NSWTC testing facility. By subtracting the
local interferences (like obstacles and roughness) present in the reference site, a site-
independent characterization of the local wind climate is produced. “This site-
51
independent characterization of the local wind climate is called a Wind Atlas data set
or regional wind climate” (Mortensen et al., 2007). Finally, by adding the local
attributes (like obstacles and roughness) of the target site (NSWTC) to the Wind
Atlas a site-specific interpretation of the local wind climate is produced.
This section presents and discusses the steps carried out in WAsP 9.0 to predict the
wind resource at the NSWTC testing facility. A site independent Wind Atlas was
created using the airport data then local site attributes at the testing centre were
implied to predict the wind resource.
6.4.1 Data Preparation To predict wind resource at a given site using WAsP 9.0 the following set of
information is required –
• A contour map of the area
• Wind data from the airport
• A simple description of the land use in the area
• An annotated sketch of the airport buildings near the meteorological station
(Mortensen et al., 2007)
6.4.2 Creating Wind Atlas This section discusses the procedures followed to create a site independent climate
data using 10 years of wind data from Jandakot airport met-station.
6.4.2.1 Contour Map A 5-meter interval contour map of Perth was purchased from Landgate. The map was
available in drawing exchange format (*.dfx). WAsP 9.0 has a utility software called
“Map Editor” that coverts dxf format to a suitable WAsP map –file.
52
Figure 18 Showing the vector map with 5meter contour intervals used for analysis in WAsP
From a close inspection of the map it was found that the contours at the testing
facility were missing (Refer to Appendix D1.1). On consultation with Landgate, it
was advised that no contours are available for forests or open sites, which might have
been the case at the time the map was created.
6.4.2.2 Jandakot Airport Wind Data After data screening and verification, yearly excel files of Jandakot airport data were
prepared. WAsP consists of a utility software called “WAsP Climate Analyst”
which “performs analyses on time-series of meteorological data” (Mortensen et al.,
2007). The data in the excel file was arranged according to the syntax compatible
with WAsP. Syntax for the format in which data was arranged is given below-
Year Month Day Hour Minutes Seconds Wind Speed (m/s) Wind Direction (°)
YYYY AA DD HH MM SS XX.X DDD
53
The excel file was then converted to a text file and loaded in the Climate Analyst
software, to prepare a climate file with 10 years of half hourly data since 2000.
Lastly, the meteorological station was located in the contour map.
6.4.2.3 Simple Description of Land Use in the Area: Roughness Rose To prepare a site independent weather data, the roughness of the terrain must be
defined. Vegetation, built-up areas, soil, water surfaces are considered to identify
roughness of a given site (Petersen et al., 1989).
Figure 19 A 10km radius circle with centre at Jandakot met-station divided into 12 equal parts to analyse the surface roughness in each parts
A circle of 10km radius with the Jandakot met-station at the centre was divided into
12 equal sectors and overlaid on a Google Earth image as shown in figure 19 to
identify the various roughness elements in each sector.
The roughness elements were identified with the Google Earth image file of the site.
As there were various roughness elements within each sector (such as water, bush,
houses etc.), the boundaries of roughness elements respective to the meteorological
54
station in each sector were determined with the Google Earth distance measuring
tool. The roughness elements so identified were matched against the terrain surface
characteristics presented in the European Wind Atlas and their values were hence
determined (Referred to in Appendix D7). The values given to different terrain
characteristics identified in the process are as follows-
• Airport area with few buildings and trees - This is categorized as roughness
class 1 and is determined to have a roughness height of 0.03 meters.
• Suburbs - This is categorized as roughness class 3 and is determined to have a
roughness height of 0.5 meters.
• Open area with remnant vegetations and some scattered buildings - This is
categorized as roughness class 2 and is determined to have a roughness height
of 0.1 meters.
• Water surface - This is categorized as roughness class 0 and is determined to
have a roughness height of 0.0003 meters.
(Petersen et al., 1989)
Figure 20 Roughness rose prepared for the Jandakot airport based on Google Earth image and European Wind Atlas
55
Roughness type in each sector were identified and defined in the WAsP “Roughness
Rose” model shown in figure 20. The various roughness elements in each sector can
be differentiated with the change in colour.
6.4.2.4 Airport Buildings near the Met - Station: Obstacle Mapping As mentioned in section 6.1.3 if the anemometer is “closer than about 50 obstacle
heights to the obstacle and closer than about three obstacle heights to the ground”
(Mortensen et al., 2007) it is considered to be an obstacle. Mapping the obstacles
around the met-station is the final step in WAsP modelling to create a site
independent climate data set.
Figure 21 Buildings with their respective heights located at Jandakot airport (Courtesy Jandakot Airport)
A map with building heights (Referred to in Figure 21) was obtained from Jandakot
airport to perform the obstacle modelling (Refer to detailed figure in Appendix D6).
The building heights were supplied by Jandakot airport within a tolerance of 1
meter. The building width, its direction and its distance from the meteorological
56
station were measured as accurately as possible from the Google Earth image. A list
of obstacles was then created as per the headings shown in table 10.
Table 10 Showing the required parameters with their symbols to create an obstacle list
ID
Angle 1
(α1)
Radius
1 (R1)
Angle 2
(α2)
Radius
2 (R1) Height
Depth
(D) Porosity
Figure 22 Showing how to measure various parameters listed in table 9 to locate an obstacle(Mortensen et al., 2007)
In figure 22,
R1 and R1 relates to the distance of the building corner from the met-station,
whereas α1 and α2 gives the building position with respect to the North direction and
“d” represents the depth of the building.
Finally an obstacle model was created for the Jandakot airport as shown in the figure
23.
57
Figure 23 Obstacles around Jandakot airport mapped out in WAsP
6.5 Predicting Wind resource at NSWTC The Wind Atlas was created in WAsP as discussed in the above sections. This site
independent climate data was then used to predict wind resource at the NSWTC
testing facility by including the necessary local attributes in the WAsP model to
make it site specific. To do this first the NSWTC test site was located in the same
contour map (discussed above) and a roughness rose and obstacle list for the testing
site were determined.
6.5.1 Roughness Rose for NSWTC Similar steps were carried out to determine the roughness for the NSWTC testing
facility as mentioned in section 6.4.2.3. The image of the testing site and its
roughness type distribution of each sector is shown in figure 24, 25.
58
Figure 24 A circle with 10km radius was divided in 12 equal sector with the NSWTC testing pad at the centre overlaid on Google Earth image to identify the various roughness elements in each sector
Figure 25 Roughness rose prepared for the NSWTC testing site based on Google Earth image
59
6.5.2 Obstacle Lists for NSWTC Testing Site There were no obstacles identified around the site (as per the ‘obstacle’ definition in
WAsP, referred to in Section 6.1.3). Hence all the possible wind-retarding elements
were treated as roughness elements.
6.6 WAsP Results After compiling the information from the reference site (Jandakot airport) and the
target site (NSWTC testing facility) in WAsP 9.0, calculations were preformed to
make wind predictions. Following results were obtained –
Figure 26 Screenshot of the predicted wind resource results by WAsP model for NSWTC testing facility
As shown in figure 26, the average wind speed as predicted by a WAsP model at the
NSWTC test site was found to be 4.29m/s at 10magl with the Weibull scale
parameter “A” at 4.8 m/s and Weibull shape parameter “k” at 1.99.
60
Figure 27 WAsP predicted wind rose for NSWTC
44% of the wind is predicted to be flowing from the South-West direction over a
year. Likewise the highest mean wind speeds (up to 6.33 m/s) are also predicted in
the same direction. The Easterlies also dominate the wind frequency table accounting
for 11.4% of the overall distribution (Refer to Appendix D2). Further, the wind rose
(Refer to Figure 27) also shows that the South-East and North-West winds have
relatively low occurrences. The predicted results are in close agreement with the
average wind direction pattern observed in Perth. During the day when the land heats
up, Perth experiences strong sea breeze from the coast (South-West). It has been
identified that the “sea breeze occurs over two-thirds of the days between the months
of November to February and can reach wind speeds of more than 20 knots
(10.3m/s)” (McMillan, 2010).
6.7 WAsP Model Validation The real measurement recorded on site with the preliminary wind monitoring system
(Refer to Section 4.1.1) was used to validate the WAsP model. The real field
measurements were compared to the results predicted by the model. The frequency
N
W E
S
61
of wind speed binned at 0.5m/s interval and the wind rose distribution over 12 equal
sectors within 360 degrees was compared to validate the WAsP model.
Methodology
September to December 2009 data extracted from the Jandakot airport climate file
was used in the WAsP model created previously to predict the wind resource at
NSWTC at 10magl over the same period as the field measurements were taken
(Refer to Section 4.1.1). The results from the WAsP model was compared with the
results obtained from real measurements (Refer to Section 4.1.1) for model
validation.
6.7.1 Data Preparation for Validation As the obstacles list and roughness rose is same, the only data that needed to be
altered in the WAsP model was the climate file. September to December 2009
climate data was extracted from the Jandakot airport database and then plugged into
the WAsP model (Created in Section 6.4).
6.7.2 Results Calculations were preformed on the WAsP model and results were obtained as show
in figure 28.
62
Figure 28 Screenshot of the predicted wind resource results by WAsP model for NSWTC testing facility using September to December 2009 wind data
The average wind speed was predicted to be 4.82m/s with the Weibull scale
parameter “A” at 5.2 m/s and Weibull shape parameter “k” at 2.15 at 10magl. Since
WAsP doesn’t produce a wind speed-binning table (As Table 4, in Section 4.1.1), the
shape and scale parameter was used to calculate the Weibull probability density
function for respective mean speed at each bin interval. The Weibull probability
density function (f (v)) can be calculated as-
−
=
− kk
Av
Av
Akvf exp)(
1
Equation 2
Where, v is the mean wind speed
The Weibull curve is continuous so it is assumed that the probability density function
gives relatively accurate frequency estimates of the wind speeds within the curve
(Weisser, 2003). However, the probability density function has limitations; it doesn’t
accurately represent the probabilities of very low wind speeds (Weisser, 2003). The
table in appendix D3 was prepared to calculate the Weibull probability density
63
function and the wind speed frequency at their respective wind bin intervals. The
total wind speed frequency was based on the number of valid data points identified
for the real measured data at the site i.e. 15851 over a 4-month period.
Figure 29 Predicted wind rose for NSWTC prepared for WAsP model validation
In figure 29, the wind rose diagram shows that the most prevailing predicted wind
direction is South-West during September to December at the NSWTC testing site.
The wind direction frequency is shown in a tabular format in Appendix D3.
6.7.3 Comparison between Results Obtained from Predicted and Real Measurements Table 11 shows the comparison of the wind frequency distribution prepared from the real measurements at NSWTC and the WAsP model.
Table 11 Comparing the results of wind frequency distribution obtained from real measurements and WAsP prediction at NSWTC
Bin Min (m/s)
Bin Max (m/s)
Wind Speed m/s
Wind Speed Frequency (NSWTC)
Wind Speed Frequency (WAsP Model)
% Deviation from Real Measurements
0.25 0.75 0.5 311 220 29% 0.75 1.25 1 423 478 -13%
N
S
W E
64
1.25 1.75 1.5 671 732 -9% 1.75 2.25 2 874 961 -10% 2.25 2.75 2.5 1124 1147 -2% 2.75 3.25 3 1135 1281 -13% 3.25 3.75 3.5 1265 1356 -7% 3.75 4.25 4 1265 1372 -8% 4.25 4.75 4.5 1317 1333 -1% 4.75 5.25 5 1312 1249 5% 5.25 5.75 5.5 1240 1131 9% 5.75 6.25 6 1019 991 3% 6.25 6.75 6.5 877 842 4% 6.75 7.25 7 718 693 3% 7.25 7.75 7.5 643 555 14% 7.75 8.25 8 462 431 7% 8.25 8.75 8.5 393 325 17% 8.75 9.25 9 278 238 14% 9.25 9.75 9.5 213 170 20% 9.75 10.25 10 153 118 23%
10.25 10.75 10.5 87 79 9% 10.75 11.25 11 66 52 21% 11.25 11.75 11.5 63 33 48% 11.75 12.25 12 32 20 36% 12.25 12.75 12.5 27 12 54% 12.75 13.25 13 12 7 40% 13.25 13.75 13.5 5 4 18% 13.75 14.25 14 6 2 62% 14.25 14.75 14.5 4 1 69% 14.75 15.25 15 2 1 68% 15.25 15.75 15.5 2 0 84% 15.75 16.25 16 1 0 84%
65
Figure 30 Graph comparing the wind speed frequency at 10magl, prepared with the real measurements taken at NSWTC and WAsP predicted model
From figure 30, the wind speed frequency occurrences (% data points) at 10magl
were prepared from the measurements taken at NSWTC and results from the WAsP
predicted model. It can be seen that deviations from real measurements with respect
to the WAsP prediction are at a reasonable match. The dominant wind bins (2m/s -
6.5m/s) have deviations from -13 to 4%. The bins with larger deviation have fewer
data points to compare. Hence it can be concluded that the larger deviations in the
results are observed, due to a small number of data points available for comparison.
Further, the predicted average wind speed for September to December was 4.82m/s
while the real measurement showed 4.83m/s, the deviation being less than 0.01%.
Table 12 Comparison of wind rose obtained from WAsP prediction and real measurement
Direction
Bin min (Degrees)
Bin max (Degrees)
Bin mid (Degrees)
Wind climate frequency (NSWTC) [%]
Wind climate frequency (WAsP)[%]
% Deviation from Real Measurements
N 345 15 0 1.7 3.3 -94%
15 45 30 2.3 3.8 -65%
66
45 75 60 1.8 4.5 -150%
E 75 105 90 6.6 8.5 -29%
105 135 120 12.4 10 19%
135 165 150 14 7 50%
S 165 195 180 14.2 12.2 14%
195 225 210 12.6 13.5 -7%
225 255 240 17.1 15.6 9%
W 255 285 270 8.7 10.9 -25%
285 315 300 6.3 6.6 -5%
315 345 330 2.2 4.1 -86%
Figure 31 Graph comparing the wind direction occurrences at 10magl, prepared with the real measurements taken at NSWTC and WAsP predicted model
Figure 31 shows a graph comparing the wind direction occurrences (% of data
points) at 10magl, prepared with the real measurements taken at NSWTC and results
from the WAsP predicted model. It can be seen that the overall trend of the real and
predicted wind direction is similar expect for 150° (South-East) where it drops
slightly. Both the predicted and real measurements have the highest frequency
67
distribution over the range of 90° to 300°, which is the direction for the prevailing
winds in Perth. The most prevailing wind direction in Perth is Easterlies and South-
westerlies. The predicted results are within a reasonable agreement with the real
measurements within this range. However, the wind distribution outside the
prevailing wind direction is relatively lower and hence larger deviations are
observed. The discrepancies found between the real and predicted results can be the
outcome of limitations within the software and data inputs, these are further
discussed in Chapter 8.
From the analysis made above, it is realised that further real data (at least one year)
are required to establish confidence in the WAsP model. Nonetheless, the model
predictions for wind speed and directions are within a reasonable accuracy. It is
therefore concluded that the WAsP model can be used as a tentative guide to longer -
term predictions at the NSWTC test site.
68
7. Assessing NSWTC Test Site Limitations This chapter discusses the limitations of the NSWTC test site for power
performance testing. To assess the limitations of the site the following questions
raised in section 1.4 were addressed using the methodology in section 2.2 –
• Types of turbines that can be tested, which meet the criteria set by the
IEC61400-12-1 and the BWEA standard
• Suitable times of the year for testing to satisfy the criteria set by the
IEC61400-12-1 and the BWEA standard
• Overall length of time required to complete the test in accordance
with the IEC61400-12-1 and the BWEA standard
Types of turbines that can be tested, which meet the criteria set by IEC61400-12-1
and the BWEA standard
A WAsP model can predict wind resource at various heights. In order to determine
the heights at which the wind predictions should be made upon consultation with the
NSWTC Manager was sought. He suggested that 18 meters is a common height for
the size of turbines aimed to be tested and the turbine tower comes at sections of 6
meters.
Considering the suggestions given, the wind resource at NSWTC was predicted at 3
different heights - 12m, 18m and 24m, using the WAsP model (with 10years of
reference data from Jandakot airport) as discussed in chapter 6.
Since WAsP doesn’t produce a wind speed-binning table, the shape and scale
parameter was used to calculate the Weibull probability density function for
respective mean speed at each bin interval using the equation 2 (Refer to Section
6.7.2). Using the probability density function, annual database of minutely sampled
wind speed bins in accordance to the IEC61400-12-1 and the BWEA standard
69
guidelines as mentioned in section 3.4 was created. The tabular representation of
annual predicted wind speed bins at 12m, 18m and 24m is in Appendix D4.
According to the IEC61400-12-1 and the BWEA standard - a complete wind speed
bin (Refer to Section 3.4) valid for power performance analysis must have at least 10
minutes of samples. The highest complete wind speed bin predicted with WAsP at
the three different heights is summarised in table 13 (Refer to Appendix D4).
Table 13 Showing the predicted highest complete wind speed bins respective to their heights of measurements
Height (m) Max. Filled wind bin
complying to standard
12 16 m/s
18 17m/s
24 18m/s
Another piece of information required in identifying the type of turbine is to find out
the range of wind speed bins required to complete the power performance test
according to the IEC61400-12-1 and the BWEA standard. As mentioned in section
3.4, a complete data set will cover the following criteria –
For IEC61400-12-1
• “Wind speed range extending from 1m/s below cut-in speed to 1.5 times the
wind speed at 85% of the rated power of the wind turbine” (IEC, 2005, p. 19)
• The wind speed bins have to be at intervals of 0.5m/s and the mid of bin
ranges have to be multiples of 0.5m/s (IEC, 2005, p. 19)
70
For BWEA
• “ The database shall include 10 minutes of data for all wind speeds at least
5m/s beyond the lowest wind speed at which power is within 95% of
maximum power or when sustained output is attained” (BWEA, 2008, p. 7)
Using the guidelines of the standards as discussed above and the findings in table 13,
table 14 summarises the type of wind turbine that can be fully tested to the standards
at NSWTC at hub heights of 12m, 18m and 24m.
Table 14 Showing the predicted range of wind turbines that can be tested at NSWTC at 3 different heights
Hub Height Turbine Type Remark
12m 85% of the turbine rated
power occurs at a wind
speed <=10.67m/s11
Satisfies the wind bins according
to IEC61400-12-1
95% of the turbine rated
power occurs at a wind
speed <=11 m/s12
Satisfies the wind bins according
to BWEA
18m 85% of the turbine rated
power occurs at a wind
speed <=11.33m/s13
Satisfies the wind bins according
to IEC61400-12-1
95% of the turbine rated
power occurs at a wind
speed<=12 m/s 14
Satisfies the wind bins according
to BWEA
11 Maximum wind speed at 12m is 16m/s, maximum wind speed bin range 16/1.5 = 10.67m/s 12 Maximum wind speed at 12m is 16m/s, maximum wind speed bin range 16-5 = 11m/s 13 Maximum wind speed at 18m is 17m/s, maximum wind speed bin range 17/1.5 = 11.33m/s 14 Maximum wind speed at 18m is 17m/s, maximum wind speed bin range 17-5 = 12m/s
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24m 85% of the turbine rated
power occurs at a wind
speed<=12m/s15
Satisfies the wind bins according
to IEC61400-12-1
95% of the turbine rated
power occurs at a wind
speed<=13 m/s 16
Satisfies the wind bins according
to BWEA
Table 14 shows the predicted range of wind turbine types on which complete power
performance tests can be performed at the NSWTC testing facility. The prediction
results shows, that there is a limitation to testing wind turbines at the test site. In the
absence of availability of real data at the test site, the above-predicted results can be
used as a guideline in turbine selection. Nonetheless, the WAsP model should be
validated against annual data, which can be collected over time, and revisions should
be made thereafter if necessary.
Suitable times of year for testing and overall time period for testing to satisfy the
criteria set by IEC61400-12-1 and the BWEA standard
The next question of importance is what time of the year is suitable for testing and
how long would it take to test the turbines. As we know the wind speed fluctuates
throughout the year, and months with high average wind speed may not be
necessarily the months with maximum wind speed. It is also understood that to
perform a power performance test, a wide range of wind speed is required.
The graph below shows average monthly wind speed and maximum wind speed over
10 years period measured at Jandakot airport. Though the wind speed measured at
15 Maximum wind speed at 24m is 18m/s, maximum wind speed bin range 18/1.5 = 12m/s 16 Maximum wind speed at 24m is 18m/s, maximum wind speed bin range 18-5 = 13m/s
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Jandakot airport will be different to the NSWTC test site, the graph provides useful
information on season fluctuation of wind speed over a year.
Figure 32 Monthly maximum and average wind speed recorded at Jandakot airport over 10 years
It can be seen from figure 32 that the higher average wind speeds are observed from
November to February (warm months where consistent sea breeze is experienced),
while lower averages are from May to August (winter months where occasional
storms are experienced). The maximum wind speeds are recorded from April to
August.
The graph provides a general idea on the maximum and average wind speeds over a
year, however to investigate in detail the time period required to test a turbine, WAsP
a analysis was performed.
A set of individual monthly files over 10 years was extracted from Jandakot airport
data, for example 10 year of all January data, 10 year of February and so on. Then
WAsP compatible climate files were created for each set of data. Using the validated
WAsP model for the NSWTC testing site, minutely wind prediction at 18magl for
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each month over a year was made. Appendix D5 shows the predicted minutely wind-
bins tables at 18magl for individual months at the NSWTC test site. Keeping in mind
the limitations on turbine selection as discussed before, it can be clearly seen in the
graph (figure 33) that June-September are ideal months to test turbines that have
higher wind-bins requirements as they have higher wind speed.
Figure 33 Graph prepared from the WAsP predicted monthly wind speed frequency results at 18magl at NSWTC test site
These sets of predicted wind-bin tables over different months provides tentative
answers to important questions that needs to be addressed prior to carrying out any
turbine test, these are-
• How long will it take to perform a power performance test on a given
turbine?
To complete the required wind bins recommended in the standards to test any
given turbine - The predicted wind availability over individual months can be
used as a guiding tool. This will provide a tentative idea of how long a
turbine might take to complete the power performance test.
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• Given a turbine what are the suitable months to start the power performance
test?
In general as the power rating of a turbine increases, the required wind speed
range for testing also increases. As the requirement to complete a power
performance test is dependent on the rated wind speed of any given turbine, it
becomes essential to test it at the right time of the year. The predicted
monthly wind availability gives a tentative idea on what wind speed bins
might be filled in the respective months.
An example of how to use the monthly predicted wind bins on estimating the time
period required to test a turbine in accordance to the IEC61400-12-1 standard
A 3kW Westwind turbine has the following specifications (Westwind, 2010) –
Table 15 Specification of a 3kW Westwind Turbine
WestWind Machine 3kW
85% power rating 12m/s
cut-in Speed 2.5m/s
The minimum wind bin required according to the IEC61400-12-1 standard is 1.5m/s
(which is 1m/s below the cut-in speed), likewise the maximum wind speed bin
required is 18m/s (which is 1.5times the wind speed at which the turbine produces
85% of the rated power).
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Now by referring to the predicted monthly minutely wind-bins, as shown in the table
below, estimates can be made on when to test the turbine and how long would it take
to test it –
Table 16 Showing the predicted minutely database of wind resource at NSWTC test site for individual months
Mid-Bin Range Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
0.5 138 111 259 778 1571 1703 1806 1806 1081 551 187 141 1 429 365 720 1622 2604 2588 2633 2633 1781 1167 529 430
1.5 826 723 1287 2410 3342 3162 3146 3146 2312 1768 959 819 2 1295 1157 1902 3077 3815 3498 3436 3436 2700 2315 1439 1274
2.5 1804 1637 2511 3576 4047 3639 3551 3551 2957 2776 1932 1763 3 2315 2127 3061 3882 4069 3622 3529 3529 3096 3130 2403 2253
3.5 2790 2587 3503 3989 3920 3483 3401 3401 3132 3364 2818 2709 4 3191 2980 3802 3910 3644 3253 3196 3196 3079 3473 3148 3096
4.5 3488 3269 3935 3676 3282 2965 2940 2940 2955 3463 3369 3386 5 3657 3431 3898 3325 2873 2643 2654 2654 2775 3346 3468 3557
5.5 3686 3452 3703 2900 2449 2309 2356 2356 2557 3141 3443 3599 6 3577 3334 3379 2444 2038 1981 2059 2059 2315 2870 3300 3513
6.5 3345 3092 2963 1992 1658 1670 1774 1774 2062 2555 3059 3310 7 3015 2754 2498 1572 1319 1386 1508 1508 1808 2219 2742 3012
7.5 2620 2356 2025 1202 1027 1133 1265 1265 1562 1881 2379 2648 8 2194 1934 1579 891 784 912 1050 1050 1332 1558 1997 2249
8.5 1770 1523 1183 640 587 724 861 861 1120 1261 1622 1844 9 1375 1149 852 447 431 568 698 698 930 997 1275 1460
9.5 1028 830 589 302 311 439 560 560 762 771 969 1115 10 739 574 391 198 220 335 445 445 618 584 713 821
10.5 510 379 249 126 153 253 350 350 495 432 506 583 11 338 239 152 78 104 189 273 273 391 313 348 399
11.5 215 144 89 47 70 139 211 211 306 222 230 263 12 131 82 50 27 46 101 161 161 237 154 147 166
12.5 77 45 27 16 30 73 122 122 182 104 91 101 13 43 23 14 9 19 52 92 92 138 69 54 59
13.5 23 11 7 5 12 37 69 69 103 45 31 33 14 12 5 3 2 7 26 51 51 77 29 17 18
14.5 6 2 1 1 5 18 37 37 56 18 9 9 15 3 1 1 1 3 12 27 27 41 11 5 5
15.5 1 0 0 0 2 8 20 20 30 7 2 2 16 0 0 0 0 1 5 14 14 21 4 1 1
16.5 0 0 0 0 1 4 10 10 15 2 0 0 17 0 0 0 0 0 2 7 7 10 1 0 0
17.5 0 0 0 0 0 2 5 5 7 1 0 0 18 0 0 0 0 0 1 3 3 5 0 0 0
18.5 0 0 0 0 0 1 2 2 3 0 0 0 19 0 0 0 0 0 0 2 2 2 0 0 0
19.5 0 0 0 0 0 0 1 1 2 0 0 0 20 0 0 0 0 0 0 1 1 1 0 0 0
20.5 0 0 0 0 0 0 1 1 1 0 0 0 Check for max bin YES YES YES YES
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Table 16 shows the predicted minutely database of the wind resource at the NSWTC
test site for individual months. The highlighted rows show the required minimum
and maximum wind speed range to test the turbine i.e. from 1.5m/s to 18m/s. The
required minimum (with at least 10minutes of data i.e 10 data points) valid wind
speed range is filled through out the year, but the maximum required bins are only
filled from June to September. As at least 10 data points are required in each bin to
make the test complete, the test has to be carried out over 4 months (June to
September) to complete the maximum bin.
So it can be estimated that - for the power performance testing on a 3kW Westwind
Turbine at the NSWTC test site, June to September are the most crucial months, and
the minimum time period required to complete the test is 4 months.
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8. Discussion & Recommendations The findings of the report can be categorized in two parts as per the objectives stated
in section 1.4.
1. Identifying the site requirements, monitoring instrumentations and their
positioning
Site Requirements
The findings in section 4.3 show that, the NSWTC test site does not comply with the
requirements mentioned in the IEC61400-12-1 standard. It is recommended that
NSWTC should perform site calibration as per the requirements of IEC61400-12-1
Annex C. The motive behind site calibration is to ensure that there is a minimum
discrepancy between the wind speed measurements taken at the meteorological-mast
and the turbine hub.
Monitoring Instruments
Monitoring instruments are the heart of the power performance test. The wrong
selection of instruments can raise questions as to the integrity of the test. In this
report, well-known instrument manufacturers were compared against the IEC61400-
12-1 and the IEA (proposed) instrument requirements to recommend a list of
instruments to NSWTC for testing turbines. While selecting the instruments both the
requirements (IEC and IEA) were equally valued and a conclusive list of equipment
was recommended to NSWTC. Before the outcome of this report monitoring
instruments were previously purchased. However the findings of this dissertation
shows that not all the equipment purchased meets IEC61400-12-1 standards. It is
recommended that NSWTC should consider purchasing the monitoring equipment
list suggested in the dissertation for valid turbine test with the IEC61400-12-1
standard.
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Mounting of instruments in the met-mast or the turbine tower
At present the maximum possible rotor diameter that can be tested on site is limited
to 3.5 meters. However, the test centre aims to test turbines up to 5 meters in rotor
diameter. It is suggested that installing an extended boom on the existing
meteorological mast will allow NSWTC to test wind turbines up to a 5 meters rotor
diameter without major modification or high cost. The arrangement assembly can be
quickly changed according to need and hence will also save significant time and cost
relative to the first option (i.e. laying out a new concrete foundation) (Refer to
Section 5.6).
2. Assessing the NSWTC test site limitations with WAsP wind modelling
To assess the NSWTC test site limitations, a WAsP model was created (Refer to
Chapter 6 and 7). The model was validated against real field measurements taken at
the test site. The WAsP predicted results showed a reasonable match with real field
measurements. However there were a few disparities due to the limitations within the
model and in the data inputs. A list of limitations are discussed below which might
have influenced the results -
• While creating the WAsP model the contour map acquired from Landgate did
not have details of the terrain of the NSWTC testing facility (Appendix
D1.1). The reason provided by a senior geospatial data consultant at Landgate
was that contours are not generated if they fall under dense vegetation or
open cut land (eg. Landfills), which may have been the case at the time the
map was created. The lack of terrain details can be one of the cases due to
which the prediction of wind direction deviated from real measurements.
• Mechanical turbulence (due to changes in surface roughness) is modelled in
WAsP but not convective turbulence (due to thermal mixing). Errors can also
occur due to the non-standard atmospheric conditions. These can be
79
atmospheric stability, diurnal sea breezes, down slope winds, blocking or
channelling in valleys (Bowen & Mortensen, 1996)
• Taking Google Earth as a reference image, the roughness rose for the WAsP
model was created. The estimation of roughness with this method is very
coarse. For a more accurate roughness estimation, a map with more detail
(including area of building covers, vegetation and their kind etc.) is required.
• “The direction rose is often divided into 12 equal direction sectors. Steep,
oblique ridges affect the direction of the incident flow and may cause the
wind direction at the predicted site to fall into an adjacent direction sector to
that occurring at the reference site”. (Bowen & Mortensen, 1996)
• WAsP can only model up to 50 obstacles in one list, Jandakot airport has
more than 50 surrounding buildings, and during the analysis the multiple
close buildings were assumed to be single due to the modelling constraint.
• Inadequate real field data (only 4 months) for comparisons
Considering the limitations (internal and external to the software) and using a
relatively small set of data, the model has shown reasonable agreement between the
predicted and real measurements (Refer to Section 6.7.3). Thus, the predicted results
from the WAsP model can be used as a tentative guide for longer term prediction at
the NSWTC test site which will provide assistance in identifying the limitations as
well as managing turbine testing schedules (Refer to Chapter 7).
8.1 Summary of Recommendations The recommendations made to NSWTC based on findings of the report are as
follows-
• A site calibration is required at the NSWTC testing facility to meet the
IEC61400-12-1 standard.
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• Instruments can be mounted on a boom to carry out measurements for
turbines with a rotor diameter greater than 3.5 meters and less then or equal
to 5 meters.
• Some of the monitoring instruments have to be repurchased to test in
accordance to the IEC61400-12-1 standard. For example- NSWTC should
reconsider on purchasing cup anemometer with class type better than 1.7A, to
comply with the IEC61400-12-1.
• The predicted wind availability over individual months can be used as a tool
to estimate suitable time of the year and overall length of time required to
complete the power performance test for a given turbine.
8.2 Future Work To give continuation to the work carried out in this dissertation potential future
works identified are as follows-
• Carry out site calibration at the NSWTC test facility to comply with the
IEC61400-12-1
• Validate the WAsP model with at least a year of real measured data
• Create a WAsP model with map that contains detailed contours of NSWTC
test site
• Map out roughness elements with higher detailed reference maps
• Prepare an excel tool based on the findings of this report to estimate the time
period and suitable months for power performance testing at the NSWTC test
site for any given turbine
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9. Conclusion The purpose of this report was to advise the National Small Wind Turbine Centre
(NSWTC), on the requirements and limitations to conduct the power performance
testing of SWTs. This was addressed through 2 objectives which were-
1st objective –Assessing the requirements for power performance testing
• Checking test site compatibility with the IEC61400-12-1 standard
• Recommending brands of monitoring instruments by using the
IEC61400-12-1 standard and IEA proposed selection criteria
• Recommending appropriate designing for positioning of monitoring
instruments by using the IEC61400-12-1 standard as a tool
2nd objective – Assessing the test site limitations to identify factors that will assist to
manage the power performance test schedule at the test site such as-
• Types of turbines that can be tested, which meet the criteria set by
IEC61400-12-1 and the BWEA standard
• Suitable times of the year for testing to satisfy the criteria set by
IEC61400-12-1 and the BWEA standard
• Overall length of time required to complete the test in accordance to
IEC61400-12-1 and the BWEA standard
The report concludes that –
• Site calibration at the NSWTC test site is required in order to comply with the
IEC61400-12-1 standards.
• Some of the monitoring instruments have to be repurchased to test in
accordance to the IEC61400-12-1 standard. For example- NSWTC should
82
reconsider purchasing a cup anemometer with a class type better than 1.7A,
to comply with IEC61400-12-1.
• The mountings of monitoring instruments can be arranged without major
modification to test up to a 5 meter rotor diameter. Beyond this, special
arrangements have to be made such as laying out a new concrete foundation
for a meteorological mast.
• The WAsP prediction results show, power performance tests can only be
carried out on a limited range of wind turbines because the required wind
bins are highly unlikely to be complete for turbines falling outside the range.
Further, the predicted wind bins for individual months of the year should be
considered for approximating a time period of the test, selecting a suitable
month to begin the test and also for preparing test schedules of different
turbines over a year.
In the absence of real data at the test site, it is recommended that NSWTC should
initially consider the predicted results when selecting turbines for testing. Future
decisions on turbine selection should be based on the meteorological data collected at
the site over at least a year in conjunction with the WAsP model.
83
10 References AWEA. (2009). AWEA Small Wind Turbine Global Market Study. Washington DC:
AWEA. A.P.C.S. (2010). Ac Active Power Transducer - AWT190. Retrieved 10 February, 2010, from http://www.apcs.net.au/products/premier/awt190.html Bailey, B. H., & McDonald, S. L. (1997). Wind Resource Assessment Handbook -
Fundamentals for Conducting a Successful Monitoring Program. Retrieved 21 January, 2010, from http://www.nrel.gov/wind/pdfs/22223.pdf
Bergey. (2009). UK Field Trial of Building Mounted Wind Turbines Shows Very Poor Results: Warwick Wind Trails. Retrieved 20th August, 2009 from http://www.bergey.com/Technical/Building.Mounted.Turbines.Warwick.Trials.html
Bowen, A. J., & Mortensen, N. G. (1996, 20-24 May). Exploring the Limits of WAsP The Wind Atlas Analysis And Application Program. Paper presented at the European Union Wind Energy Conference, Goteborg, Sweden.
BWEA. (2008). British Wind Energy Association Small Wind Turbine Performance and Safety Standard (Standard). London: BWEA.
Datataker. (2010). Dt80 Series2 datalogger. Retrieved 12 February, 2010, from http://www.datataker.com/Library/Product_Data_Sheets_TS/TS-0059-E1%20-%20DT80.pdf
Enercon. (2009). E-82. Retrieved 14 April, 2010, from http://www.enercon.de/en/_home.htm
Gipe, P. (1997). The Need for an International Small Wind Turbine Test Center [Electronic Version]. Retrieved 2nd September 2009 from http://www.wind-works.org/articles/NeedTest.html.
IEA. (2008). Task 27 Summary Page: Consumer Labelling of Small Wind Turbines. Retrieved 2nd September 2009, from http://www.ieawind.org/Summary_Page_27.html
IEC. (2005). Wind turbines - Part 12-1: Power performance measurements of electricity producing wind turbines (Standards No. 61400-12-1). Geneva: International Electotechnical Commission.
Instruments, V. (2010). A100LK/A100LM Low-Power Anemometers (pulse/frequency output). Retrieved 6 February, 2010, from http://www.windspeed.co.uk/ws/index.php?option=displaypage&op=page&Itemid=52
Lee, G. (2008). Wind Resource Analysis Report. McMillan, D. (2010). David McMillan's ATC Retrieved 20 February 2010, from http://users.ssc.net.au/mcmillan/ATC%20in%20WA/3_geography_and_weather_at_perth.htm Mortensen, N. G., Heathfield, D. N., Myllerup, L., Landberg, L., & Rathmann, O.
(2007). WAsP 9 Help Facility and On-line Documentation. NRG. (2008a). NRG #40C Anemometer, Measnet Calibrated. Retrieved 6
February, 2010, from http://www.nrgsystems.com/sitecore/content/Products/4350.aspx?pf=StandardSensors
NRG. (2008b). NRG #200P Wind Direction Vane, 10K, With Boot. Retrieved 6 February, 2010, from http://www.nrgsystems.com/sitecore/content/Products/1904.aspx?pf=StandardSensors
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NRG. (2008c). NRG #BP20 Barometric Pressure Sensor. Retrieved 6 February, 2010, from http://www.nrgsystems.com/sitecore/content/Products/2046.aspx?pf=StandardSensors
Onset. (2010). S-BPB-CM50 Barometric Pressure Smart Sensor. Retrieved 7 February, 2010, from http://www.onsetcomp.com/products/sensors/s-bpb-cm50
Petersen, Troen, I., & Lundtang, E. (1989). European Wind Atlas. Roskilde: Riso National Laboratories.
PEC590. (2008). Design of Wind Power System. RISO. (2010). Summary if Cup Anemometer Classification According to IEC61400-
12-1 CDV requirements. Retrieved 6 February, 2010, from http://www.cupanemometer.com/technical/P2546%20Classification%20IEC61400-121CDV.pdf
RM.Young. (2008a). PRECIPITATION//PRESSURE. Retrieved 6 February, 2010, from http://www.youngusa.com/products/3/22.html
RM.Young. (2008b). TEMPERATURE//HUMIDITY. Retrieved 6 February, 2010, from http://www.youngusa.com/products/2/15.html
Vaisala. (2010a). Vaisala HUMICAP® Humidity and Temperature Probe HMP155. Retrieved 6 February, 2010, from http://www.vaisala.com/weather/products/hmp155.html
VAISALA. (2010b). Vaisala Wind Set WA15. Retrieved 6 February, 2010, from http://www.vaisala.com/weather/products/wa15.html
Vector. (2010). W200P Potentiometer Windvane. Retrieved 6 February, 2010, from http://www.windspeed.co.uk/ws/index.php?option=displaypage&op=page&Itemid=61
WAsP.(2010).WAsP-the Wind Atlas Analysis and Application Program. Retrieved 15 April,2010, from http://www.wasp.dk/
Weisser, D. (2003). A wind energy analysis of Grenada: an estimation using the ‘Weibull’ density function. Renewable Energy l28 (11), 1802-1812.
Westwind. (2010). Products - 3kW Westwind. Retrieved 7 March, 2010, from http://www.westwindturbines.co.uk/products/3kwwindturbine.asp Whale, J. (2008). PEC590 Energy Systems: Design of Wind Power Systems. Whale, J. (2010). Site Selection for NSWTC. In A. Malla (Ed.). Perth. Whale, J., & Brix, B. (2009, 2009). The National Small Wind Turbine Center:
Activities in Standards and Labelling. Paper presented at the 47th ANZSES Annual Conference, Townsville, Queensland, Australia.
WINDSENSOR. (2010). Products. Retrieved 6 February, 2010, from http://www.cupanemometer.com/products.htm
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11 Appendix
Appendix A Site Requirements
A1 Scoring Criteria for Site Assessment
Table 17 Categories used in the formulation of the score card for assessing sites(Whale, 2010)
Rank Category Subcategories 1. Wind Resource Wind Speed; Terrain; Obstacles 2. Risk Security; Safety 3. Land Characteristics Area; Topography/Ground Surface; Development Requirements 4. Partner/Landlord
Requirements Tenure; Lease Cost/Occupancy Cost
5. Accessibility Access for Works; Access for Researchers/Students 6. On- Site Resources People and Buildings; Power and Communications
A2 Survey Map for NSWTC Test Site In next page
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87
Appendix B Monitoring Instruments
B1. Davis Instrument
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B2 Cup Anemometer It is the most important instrument in the power performance monitoring system. A
cup anemometer is used for measuring wind speed. There is large range of cup
anemometer available in the market varying in performance and cost. The cheapest
among the range of well know cup anemometers is the NRG #40, but this has a low
frequency output, for higher frequency outputs anemometers from manufacturer like
– Vaisala, Vector instruments are often preferred. These cup anemometers are also
calibrated to the IEC61400-12-1 standard, which makes them preferable choice
among majority of testers around the globe.
Information from the anemometer manufacturer’s websites, along with consultation
with the Field and Data Operation Manager of Wind Monitoring Service at CSIRO
(Marine and Atmospheric Research Australia) and Technical officer at RISE
Institute, Murdoch University, following list of cup anemometers was prepared–
NRG #40 –“A four-pole magnet induces a sine wave voltage into a coil producing an
output signal with frequency proportional to wind speed”(NRG, 2008a). It has
response of one pulse every second. It can measure wind speed at a range of 0-
96m/s. They are cheap (AUD$427) and particularly used for assessment of potential
noise propagations and measuring wind resource for a site. They can be purchased
with Measnet calibration.(NRG, 2008a)
The technical specification details as provided by the manufacturer of the sensor is -
89
90
91
VectorA100LM – It is highly sensitive yet robust 3-cup anemometer with photo-
electronic pulse generator and ratemeter (Instruments, 2010). The output is in DC
voltage, which is linear to the wind speed. It is capable of measuring wind speed
from 0-75m/s with an accuracy of 1% within a range of 10-55m/s (Instruments,
2010). CSIRO have generally used them in regions where there was concern about
significant non-horizontal winds. According to CSIRO the local support is good and
spare parts are readily available though there were some manufacture quality control
issues which had resulted in cup failures. The calibration of the anemometers is done
according to the IEC61400-12-1 standards and is traceable to national standards. The
sensor is made of anodise aluminium, stainless steels and weather resisting plastics
for exposed parts. It has corrosion resistance ball-races, which makes it suitable for
longer-term exposure to the varied weather conditions. The sensor is priced at
AUD$710 and an extra AUD$410 for calibration. (Instruments, 2010)
VA100LM is specified as class type 1.8A, and thus meets the IEC61400-12-1 class
type requirement (Refer to in Section 3.2.1). The technical specification details as
provided by the manufacturer of the sensor is -
92
93
RISǾ P2456A–According to CSIRO it is one of the top quality instruments available
in the market. The calibration of the cup anemometer is done according to the
IEC61400-12-1. It is constructed by anodised aluminium and stainless steel, which
makes it suitable for long-term exposure to, varied weather conditions. It generates 2
pulses for each revolution and “is equipped with a special built-in mechanism, which
reduces the variation in operating time over the frequency range. This feature
provides the possibility of obtaining the instantaneous wind speed by measuring the
time interval of each revolution”(WINDSENSOR, 2010). It can measure from 0 to
70m/s with an accuracy of 0.3% within range from4 to 16m/s. A DC supply of less
than 30 volts must be provided to excite the sensor. However, the cup anemometer is
very expensive(WINDSENSOR, 2010). It costs around AUSD $1600 plus a further
AUSD $650 for calibration. According to CSIRO, there are no local service options
and they have to be sent to Denmark for repairs, this means they are expensive to
maintain.
P2546A is specified as class type 1.31A, and thus doesn’t meet the IEC61400-12-1
class type requirement (Section 3.2.1) (RISO, 2010). The technical specification
details as provided by the manufacturer of the sensor is -
94
95
Vaisala WAA151 – It is an optoelectronic, fast response and low-threshold
anemometer. It has a measurement range of 0.4 to 75m/s with an accuracy of
0.17m/s within a range from 0.4 to 60m/s. It is constructed from gray anodised
aluminium magnesium silicon alloy and further reinforced with carbon fibre, which
makes it resistance to corrosion when exposed to long term monitoring in varied
weather conditions. (VAISALA, 2010b)
It is one of the commonly used anemometers by CSIRO; they have experienced it as
one of the reliable and yet inexpensive anemometers compared to RISǾ and Vector
Instruments. However during significant non- horizontal winds they are reputed to
work poorly compared to the aforementioned sensors. It also has a major
disadvantage – it requires power to operate which means that remote logging sites
require a bigger battery system compared to either a fully RISǾ or NRG
instrumented site. They are calibrated to ASTM D5096-90 standards. It is priced at
AUS$1000 (VAISALA, 2010b).
The technical specification details as provided by the manufacturer of the sensor is -
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97
B3 Wind Vane
Wind vane is used for wind direction measurements. Similar to cup anemometer
wide range of wind vane sensors are available in the market. Commonly the wind
vanes consist of a potentiometer that gives voltage signal as output, which is linear to
the wind direction (in degrees). Most of the wind vane has a dead band close to
North reading; however there are sensors available which have overcome this issue.
Some of the commonly used vanes in wind turbine testing are listed below –
Vector Instruments W200P – It consists of a potentiometer that has lowest torque
and has smooth operation over the full 360˚. It is made from anodised aluminium
alloys and stainless steel along with hard plastic bearings and precision ball-races,
which makes it suitable for exposure to longer term monitoring in varied weather
conditions. It has an advantage of operating in low power mode where the
potentiometer can be energised only for a short interval during the actual
measurement. It can measure direction within a wind speed range of 0.6m/s to
0.75m/s. it has an accuracy of 3˚ in steady winds over 5m/s. the instrument is
priced at AUD$ 828. (Vector, 2010).
Vaisala WAV151 – It consists of infrared Light Emitting Diodes (LEDs) and
phototransistors mounted on a disc, when the vane rotates it create changes in signal,
which is received by the phototransistors. It is a highly sophisticated sensor with low
threshold, counterbalance and heating elements to overcome freezing. It measures
full 360˚ range with an accuracy of 3˚. The operating power supply can be from 9.5
to 15.5 VDC. It is made from anodised aluminium alloys and stainless steel, which
makes it suitable for exposure to longer term monitoring in varied weather
conditions. (VAISALA, 2010b)
98
The technical specification details of the sensor can be found under B2 Vaisala
WAA151.
NRG 200# - It is one of the commonly used wind vane. It consists of a
potentiometer, which produces DC voltage signal as output when the vane rotates. It
is constructed form thermoplastic and stainless steel. It measure full 360˚ but has a
dead-band near North ranging from a maximum of 8˚ to a more typical value of 4˚. It
is one of the cheap wind vanes available, which costs around AUD$ 221. The sensor
can be energised with 1 to 15 VDC. It has a lifespan of 50 million revolutions (2 to 6
years normal operation).(NRG, 2008b)
The technical specification details as provided by the manufacturer of the sensor is -
99
100
101
B4 Temperature and Humidity Sensor
Temperature and humidity measuring sensor are available as a separate or integrated
unit. Integrated units is given preference in this case as it can be measured in a single
channel at the data logging unit, further the cable length will also be minimised using
single sensor instead of two different ones.
Vaisala HMP155 – The HMP155 is a humidity and temperature probe with
aluminium body. The sensor is protected by a membrane filter and plastic grid. It can
measure relative humidity within a range of 0 to 100% with an accuracy of 1%
from 0 to 90% and 1.7% from 90-100%. Similarly, for a voltage signal it has a
temperature measuring range of -80 to 60˚C with an accuracy of
˚C from -80- +20˚C and
˚C from +20 - +60˚C. The sensor can be
energized by VDC from 8 – 28V and the output signal is also in VDC ranging from 0
– 2.5V. It is priced at AUS$ 320.(Vaisala, 2010a)
The technical specification details as provided by the manufacturer of the sensor is -
102
103
RM Young Model 41382 Relative Humidity and Temperature Probe – It consists of
a precision Platinum RTD temperature sensor and a capacitance type humidity
sensor. The probe comes with two options for the output signal either 0-1VDC or 4-
20mA. It can measure relative humidity from 0- 100% with an accuracy of 2% at
20˚C. Similarly it has a temperature measuring range of -50 to 50˚C with 0.3˚C
accuracy at 0˚C. The sensor can be energised by VDC from 10 – 28V supply. It is
priced at AUD$ 824. (RM.Young, 2008b)
The technical specification details of the sensor can be found in below.
104
105
B5 Pressure Sensor
The barometric pressure measurement is a part of power performance testing, used
for deriving air density. Some of the commonly used pressure sensors available in
the market are discussed here.
NRG BP20 – It is a micro-machined absolute pressure sensor in rugged ABS
enclosure. The output is a VDC signal, which is proportional to absolute pressure. A
built in temperature compensator, linearization, and an output amplifier ensure
reliable measurements. It can measure from 15kPa to 115kPa with an accuracy of
1.5kPa. It operates at full accuracy within a temperature range of 10-50˚C. A
supply DC voltage of 7 to 35 V is required to energies the sensor. The sensor can be
purchased with calibration. The sensor is priced at AUD$ 325.(NRG, 2008c)
The technical specification details as provided by the manufacturer of the sensor is -
106
107
108
R.M. Young Model 61302V – It is enclosed by a weatherproof material and
produces VDC output ranging from 0-5V. It can measure pressure from 50kPa –
110kPa with an accuracy of 0.05%. It can operate from -40-60˚C. A DC supply
voltage from 7-30V can energies the sensor. The sensor is priced at AUD$ 650.
(RM.Young, 2008a)
The technical specification details as provided by the manufacturer of the sensor is -
109
110
Onset S-BPB-CM50 – The sensor is enclosed with weatherproof material. It can
measure pressure from 66 -107kPa over a temperature range of -40˚ to 70˚C. It has a
0.3kPa at 25˚C and 0.5kPa over a range from -40˚ - 70˚C. The output cable is
RJ45 and needs special loggers for connection. The sensor is priced at AUD$
269.(Onset, 2010)
The technical specification details as provided by the manufacturer of the sensor is -
111
112
Appendix C Measurement at NSWTC Test Site
C1 Wind Rose Measured at NSWTC Presented in Tabular Format Table 18 Showing the tabular representation of wind rose measured at NSWTC testing site
Direction
Bin min (m/s)
Bin max (m/s)
Bin mid (m/s)
Wind Direction Frequency
% of occurrences
N 0 15 7.5 135 0.84% 15 45 30 377 2.3% 45 75 60 293 2% E 75 105 90 1060 7% 105 135 120 2008 12% 135 165 150 2254 14% S 165 195 180 2287 14% 195 225 210 2040 13% 225 255 240 2758 17% W 255 285 270 1406 9% 285 315 300 1017 6% 315 345 330 357 2% 345 375 360 140 0.87%
113
Appendix D WAsP Related
D1. Reference Sites Investigated for WAsP Cockburn Cement
Figure 34 Showing location of Cockburn Cement and NSWTC test facility
Cockburn cement is located at -32.147167°S, 115.798369°E and is 2.25km aerial
distance from NSWTC testing facility. The main purpose of collecting data at
Cockburn cement is to monitor the dust emission. The monitored data is recorded on
an hourly basis and data from year 2004 to 2007 was available for analysis.
114
Figure 35 Showing the missing data recorded at Cockburn cement
The monitoring station is highly sheltered with obstacles. Two main reasons to reject
this site were due to the heavy influence of obstacles on wind measurement and
missing data.
Water Corporation Woodman Point Waste Water Treatment Plant
Figure 36 Showing location of Woodman Point and NSWTC test facility
It is located at -32.136262°S, 115.763027°N and is approximately 4.75km aerial
distance from the NSWTC testing facility. The wind parameters were recorded every
115
15 seconds and 1 year data from 2007-2008 was available. This site was not
considered suitable for analysis due to lack of data.
Medina Research Centre
Figure 37 Showing location of Medina Research Centre and NSWTC test facility
Medina Research Centre is located at -32.219940°S, 115.816290°N and is 6.15km
aerial distance from the NSWTC testing facility. The station is managed by the
Department of Agriculture and Food, and only records data at 9am and 3pm. This
met station was not considered, as using such large interval will create high
uncertainty in prediction, further it doesn’t compliment the objective of the research.
116
University of Melbourne Weather Station
Figure 38 Showing location of University of Melbourne weather station and NSWTC test facility
It is located at-32.163415°S, 115.798220°E and is 0.37km aerial distance from
NSTWC testing facility. It is the nearest met station to the NSWTC site compared to
the others discussed in this section. 1 year and two months of hourly data was
available since 2007 for this site. The measurements were taken at a height of 1.98
magl. The recorded data was missing from August to November 2008. The wind
vane was found to be in non-operating condition and large amount of invalid data
was found. According to previous analysis carried out as student work, only 60% of
the recorded data was identified as usable (Lee, 2008). Though the met station lies
extremely close to the testing facility, due to inconsistency and inadequate data this
site was not considered for the analysis.
117
Department of Environment and Conservation Hope Valley Weather Station
Figure 39 Showing location of Hope Valley Weather Station and NSWTC test facility
It is located at -32.205752°S, 115.794784°N and is 4.4km aerial distance from the
NSWTC facility.10 minutes average data was available from since 1998 to 2008,
recorded at a height of 10magl. The met station is located in an urban area and
largely surrounded by trees and large spread of bushland.
118
Kiwnana Industrial Council Fancote Avenue
Figure 40 Showing location of Kwinana Industrial Council monitoring site at Fancote Avenue and NSWTC test facility
It is located at -32.138504°S, 115.810245°N and is 3.35km aerial distance from the
NSWTC facility. 10 minutely average data was available from since 2004 to 2008,
recorded at a height of 10m. The site is located in an urban area but with very few
obstacles surrounding the met station.
119
Jandakot Airport
Figure 41 Showing location of Jandakot Airport and NSWTC test facility
Jandakot met station is located at -32.101100°S, 115.879402°E and is 10.6km aerial
distance from NSWTC testing facility. The recording station is situated in an open
area apart from terminal buildings towards North West. Half hourly data was
available since 1994 to January 2010. Further, as the meteorological station is
maintained by Bureau of Meteorology, Australia, the periodic maintenance of
monitoring instruments assures reliable data.
120
D1.1 Missing Contours of the Site
Figure 42 Missing contours at the NSWTC test site represented by a turbine symbol
D2 WAsP Wind Rose
Table 19 Showing the WAsP predicted mean wind speed and their occurrence frequency with respect to the directions
Direction Sector Sector Wind climate Wind climate Number Angle [°] Frequency [%] Mean speed [m/s] N 1 0 4.9 3.25 2 30 6.6 3.29 3 60 7.5 3.96 E 4 90 11.8 4.08 5 120 10.4 3.79 6 150 6.7 2.77 S 7 180 10.4 3.14 8 210 11.8 4.29 9 240 12.8 5.95 W 10 270 9 6.33 11 300 4.9 5.32 12 330 3.3 4.18
121
D3 Predicted Wind Bins by calculating the Weibull Probability Density Function (using data -September – December 2009) Table 20 Showing the WAsP predicted wind speeds frequencies respective to their bins determined by calculating the probability density function
Bin Min (m/s)
Bin Max (m/s)
Bin Mid (m/s)
Probability Density function
Wind Speed
Frequency 0.25 0.75 0.5 0.01 220 0.75 1.25 1 0.03 478 1.25 1.75 1.5 0.05 732 1.75 2.25 2 0.06 961 2.25 2.75 2.5 0.07 1147 2.75 3.25 3 0.08 1281 3.25 3.75 3.5 0.09 1356 3.75 4.25 4 0.09 1372 4.25 4.75 4.5 0.08 1333 4.75 5.25 5 0.08 1249 5.25 5.75 5.5 0.07 1131 5.75 6.25 6 0.06 991 6.25 6.75 6.5 0.05 842 6.75 7.25 7 0.04 693 7.25 7.75 7.5 0.03 555 7.75 8.25 8 0.03 431 8.25 8.75 8.5 0.02 325 8.75 9.25 9 0.02 238 9.25 9.75 9.5 0.01 170 9.75 10.25 10 0.01 118
10.25 10.75 10.5 0.00 79 10.75 11.25 11 0.00 52 11.25 11.75 11.5 0.00 33 11.75 12.25 12 0.00 20 12.25 12.75 12.5 0.00 12 12.75 13.25 13 0.00 7 13.25 13.75 13.5 0.00 4 13.75 14.25 14 0.00 2 14.25 14.75 14.5 0.00 1 14.75 15.25 15 0.00 1 15.25 15.75 15.5 0.00 0 15.75 16.25 16 0.00 0 16.25 16.75 16.5 0.00 0 16.75 17.25 17 0.00 0 17.25 17.75 17.5 0.00 0 17.75 18.25 18 0.00 0 18.25 18.75 18.5 0.00 0 18.75 19.25 19 0.00 0 18.75 19.25 19.5 0.00 0 18.75 19.25 20 0.00 0
122
WAsP Predicted Wind Rose at NSWTC in Tabular Format (using data -September – December 2009)
Table 21 Showing the tabular representation of wind rose predicted at NSWTC test site
Direction Wind Direction Bin min (Deg)
Wind Direction Bin Max (Deg)
Wind Direction Bin Mid (Deg)
% of occurrences
N 345 15 0 3.3 15 45 30 3.8 45 75 60 4.5 E 75 105 90 8.5 105 135 120 10 135 165 150 7 S 165 195 180 12.2 195 225 210 13.5 225 255 240 15.6 W 255 285 270 10.9 285 315 300 6.6 315 345 330 4.1
D4 Annual Predicted Wind Speed Bins for NSWTC Test Site at 12m, 18m and 24m using the Weibull Probability Density Function
At 12 meters Table 22 Showing predicted wind speed bins at 12 mgal
Bin Min (m/s)
Bin Max (m/s)
Bin Mid (m/s)
Probability Density function Wind Speed Frequency
0.25 0.75 0.5 0.019 9828 0.75 1.25 1 0.037 19239 1.25 1.75 1.5 0.053 27628 1.75 2.25 2 0.066 34552 2.25 2.75 2.5 0.076 39711 2.75 3.25 3 0.082 42955 3.25 3.75 3.5 0.084 44294 3.75 4.25 4 0.083 43871 4.25 4.75 4.5 0.080 41943 4.75 5.25 5 0.074 38834 5.25 5.75 5.5 0.066 34906 5.75 6.25 6 0.058 30511 6.25 6.75 6.5 0.049 25970 6.75 7.25 7 0.041 21547 7.25 7.75 7.5 0.033 17441 7.75 8.25 8 0.026 13781 8.25 8.75 8.5 0.020 10636 8.75 9.25 9 0.015 8021 9.25 9.75 9.5 0.011 5913 9.75 10.25 10 0.008 4262
123
10.25 10.75 10.5 0.006 3005 10.75 11.25 11 0.004 2072 11.25 11.75 11.5 0.003 1399 11.75 12.25 12 0.002 924 12.25 12.75 12.5 0.001 597 12.75 13.25 13 0.001 378 13.25 13.75 13.5 0.000 234 13.75 14.25 14 0.000 142 14.25 14.75 14.5 0.000 84 14.75 15.25 15 0.000 49 15.25 15.75 15.5 0.000 28 15.75 16.25 16 0.000 16 16.25 16.75 16.5 0.000 9 16.75 17.25 17 0.000 5 17.25 17.75 17.5 0.000 2 17.75 18.25 18 0.000 1 18.25 18.75 18.5 0.000 1 18.75 19.25 19 0.000 0
At 18 meters Table 23 Showing predicted wind speed bins at 18 mgal
Bin Min (m/s)
Bin Max (m/s)
Bin Mid (m/s)
Probability Density function Wind Speed Frequency
0.25 0.75 0.5 0.015 7694 0.75 1.25 1 0.030 15681 1.25 1.75 1.5 0.044 23180 1.75 2.25 2 0.057 29743 2.25 2.75 2.5 0.067 35041 2.75 3.25 3 0.074 38859 3.25 3.75 3.5 0.078 41105 3.75 4.25 4 0.080 41799 4.25 4.75 4.5 0.078 41068 4.75 5.25 5 0.074 39118 5.25 5.75 5.5 0.069 36211 5.75 6.25 6 0.062 32631 6.25 6.75 6.5 0.055 28665 6.75 7.25 7 0.047 24570 7.25 7.75 7.5 0.039 20567 7.75 8.25 8 0.032 16823 8.25 8.75 8.5 0.026 13452 8.75 9.25 9 0.020 10521 9.25 9.75 9.5 0.015 8051 9.75 10.25 10 0.011 6029
10.25 10.75 10.5 0.008 4419 10.75 11.25 11 0.006 3172 11.25 11.75 11.5 0.004 2229 11.75 12.25 12 0.003 1534 12.25 12.75 12.5 0.002 1034 12.75 13.25 13 0.001 683 13.25 13.75 13.5 0.001 442 13.75 14.25 14 0.001 280 14.25 14.75 14.5 0.000 174 14.75 15.25 15 0.000 106
124
15.25 15.75 15.5 0.000 63 15.75 16.25 16 0.000 37 16.25 16.75 16.5 0.000 21 16.75 17.25 17 0.000 12 17.25 17.75 17.5 0.000 7 17.75 18.25 18 0.000 4 18.25 18.75 18.5 0.000 2 18.75 19.25 19 0.000 1
At 24 meters Table 24 Showing predicted wind speed bins at 24 mgal
Bin Min (m/s)
Bin Max (m/s)
Bin Mid (m/s)
Probability Density function Wind Speed Frequency
0.25 0.75 0.5 0.012 6159 0.75 1.25 1 0.025 12960 1.25 1.75 1.5 0.037 19601 1.75 2.25 2 0.049 25669 2.25 2.75 2.5 0.059 30848 2.75 3.25 3 0.066 34910 3.25 3.75 3.5 0.072 37711 3.75 4.25 4 0.075 39202 4.25 4.75 4.5 0.075 39418 4.75 5.25 5 0.073 38471 5.25 5.75 5.5 0.070 36534 5.75 6.25 6 0.064 33816 6.25 6.75 6.5 0.058 30550 6.75 7.25 7 0.051 26964 7.25 7.75 7.5 0.044 23270 7.75 8.25 8 0.037 19647 8.25 8.75 8.5 0.031 16237 8.75 9.25 9 0.025 13139 9.25 9.75 9.5 0.020 10415 9.75 10.25 10 0.015 8088
10.25 10.75 10.5 0.012 6155 10.75 11.25 11 0.009 4591 11.25 11.75 11.5 0.006 3357 11.75 12.25 12 0.005 2407 12.25 12.75 12.5 0.003 1691 12.75 13.25 13 0.002 1166 13.25 13.75 13.5 0.001 788 13.75 14.25 14 0.001 522 14.25 14.75 14.5 0.001 339 14.75 15.25 15 0.000 216 15.25 15.75 15.5 0.000 135 15.75 16.25 16 0.000 83 16.25 16.75 16.5 0.000 50 16.75 17.25 17 0.000 29 17.25 17.75 17.5 0.000 17 17.75 18.25 18 0.000 10 18.25 18.75 18.5 0.000 5 18.75 19.25 19 0.000 3
125
D5. WAsP Predicted Wind-Bins Tables at 18magl for Each Individual Month at NSWTC Test Site
Jan Feb Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
0.25 0.75 0.5 0.003 138 0.25 0.75 0.5 0.003 111 0.75 1.25 1 0.010 429 0.75 1.25 1 0.009 365 1.25 1.75 1.5 0.018 826 1.25 1.75 1.5 0.018 723 1.75 2.25 2 0.029 1295 1.75 2.25 2 0.029 1157 2.25 2.75 2.5 0.040 1804 2.25 2.75 2.5 0.041 1637 2.75 3.25 3 0.052 2315 2.75 3.25 3 0.053 2127 3.25 3.75 3.5 0.062 2790 3.25 3.75 3.5 0.064 2587 3.75 4.25 4 0.071 3191 3.75 4.25 4 0.074 2980 4.25 4.75 4.5 0.078 3488 4.25 4.75 4.5 0.081 3269 4.75 5.25 5 0.082 3657 4.75 5.25 5 0.085 3431 5.25 5.75 5.5 0.083 3686 5.25 5.75 5.5 0.086 3452 5.75 6.25 6 0.080 3577 5.75 6.25 6 0.083 3334 6.25 6.75 6.5 0.075 3345 6.25 6.75 6.5 0.077 3092 6.75 7.25 7 0.068 3015 6.75 7.25 7 0.068 2754 7.25 7.75 7.5 0.059 2620 7.25 7.75 7.5 0.058 2356 7.75 8.25 8 0.049 2194 7.75 8.25 8 0.048 1934 8.25 8.75 8.5 0.040 1770 8.25 8.75 8.5 0.038 1523 8.75 9.25 9 0.031 1375 8.75 9.25 9 0.028 1149 9.25 9.75 9.5 0.023 1028 9.25 9.75 9.5 0.021 830 9.75 10.25 10 0.017 739 9.75 10.25 10 0.014 574
10.25 10.75 10.5 0.011 510 10.25 10.75 10.5 0.009 379 10.75 11.25 11 0.008 338 10.75 11.25 11 0.006 239 11.25 11.75 11.5 0.005 215 11.25 11.75 11.5 0.004 144 11.75 12.25 12 0.003 131 11.75 12.25 12 0.002 82 12.25 12.75 12.5 0.002 77 12.25 12.75 12.5 0.001 45 12.75 13.25 13 0.001 43 12.75 13.25 13 0.001 23 13.25 13.75 13.5 0.001 23 13.25 13.75 13.5 0.000 11 13.75 14.25 14 0.000 12 13.75 14.25 14 0.000 5 14.25 14.75 14.5 0.000 6 14.25 14.75 14.5 0.000 2 14.75 15.25 15 0.000 3 14.75 15.25 15 0.000 1 15.25 15.75 15.5 0.000 1 15.25 15.75 15.5 0.000 0 15.75 16.25 16 0.000 0 15.75 16.25 16 0.000 0 16.25 16.75 16.5 0.000 0 16.25 16.75 16.5 0.000 0 16.75 17.25 17 0.000 0 16.75 17.25 17 0.000 0 17.25 17.75 17.5 0.000 0 17.25 17.75 17.5 0.000 0 17.75 18.25 18 0.000 0 17.75 18.25 18 0.000 0 18.25 18.75 18.5 0.000 0 18.25 18.75 18.5 0.000 0 18.75 18.75
Total 1.000 44638 1.000 40319 March April Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
0.25 0.75 0.5 0.006 259 0.25 0.75 0.5 0.018 778 0.75 1.25 1 0.016 720 0.75 1.25 1 0.038 1622 1.25 1.75 1.5 0.029 1287 1.25 1.75 1.5 0.056 2410 1.75 2.25 2 0.043 1902 1.75 2.25 2 0.071 3077 2.25 2.75 2.5 0.056 2511 2.25 2.75 2.5 0.083 3576 2.75 3.25 3 0.069 3061 2.75 3.25 3 0.090 3882
126
3.25 3.75 3.5 0.078 3503 3.25 3.75 3.5 0.092 3989 3.75 4.25 4 0.085 3802 3.75 4.25 4 0.091 3910 4.25 4.75 4.5 0.088 3935 4.25 4.75 4.5 0.085 3676 4.75 5.25 5 0.087 3898 4.75 5.25 5 0.077 3325 5.25 5.75 5.5 0.083 3703 5.25 5.75 5.5 0.067 2900 5.75 6.25 6 0.076 3379 5.75 6.25 6 0.057 2444 6.25 6.75 6.5 0.066 2963 6.25 6.75 6.5 0.046 1992 6.75 7.25 7 0.056 2498 6.75 7.25 7 0.036 1572 7.25 7.75 7.5 0.045 2025 7.25 7.75 7.5 0.028 1202 7.75 8.25 8 0.035 1579 7.75 8.25 8 0.021 891 8.25 8.75 8.5 0.026 1183 8.25 8.75 8.5 0.015 640 8.75 9.25 9 0.019 852 8.75 9.25 9 0.010 447 9.25 9.75 9.5 0.013 589 9.25 9.75 9.5 0.007 302 9.75 10.25 10 0.009 391 9.75 10.25 10 0.005 198
10.25 10.75 10.5 0.006 249 10.25 10.75 10.5 0.003 126 10.75 11.25 11 0.003 152 10.75 11.25 11 0.002 78 11.25 11.75 11.5 0.002 89 11.25 11.75 11.5 0.001 47 11.75 12.25 12 0.001 50 11.75 12.25 12 0.001 27 12.25 12.75 12.5 0.001 27 12.25 12.75 12.5 0.000 16 12.75 13.25 13 0.000 14 12.75 13.25 13 0.000 9 13.25 13.75 13.5 0.000 7 13.25 13.75 13.5 0.000 5 13.75 14.25 14 0.000 3 13.75 14.25 14 0.000 2 14.25 14.75 14.5 0.000 1 14.25 14.75 14.5 0.000 1 14.75 15.25 15 0.000 1 14.75 15.25 15 0.000 1 15.25 15.75 15.5 0.000 0 15.25 15.75 15.5 0.000 0 15.75 16.25 16 0.000 0 15.75 16.25 16 0.000 0 16.25 16.75 16.5 0.000 0 16.25 16.75 16.5 0.000 0 16.75 17.25 17 0.000 0 16.75 17.25 17 0.000 0 17.25 17.75 17.5 0.000 0 17.25 17.75 17.5 0.000 0 17.75 18.25 18 0.000 0 17.75 18.25 18 0.000 0 18.25 18.75 18.5 0.000 0 18.25 18.75 18.5 0.000 0 18.75 18.75
Total 1.000 44633 0.999 43147 May June Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
0.25 0.75 0.5 0.035 1571 0.25 0.75 0.5 0.039 1703 0.75 1.25 1 0.058 2604 0.75 1.25 1 0.060 2588 1.25 1.75 1.5 0.075 3342 1.25 1.75 1.5 0.073 3162 1.75 2.25 2 0.085 3815 1.75 2.25 2 0.081 3498 2.25 2.75 2.5 0.091 4047 2.25 2.75 2.5 0.084 3639 2.75 3.25 3 0.091 4069 2.75 3.25 3 0.084 3622 3.25 3.75 3.5 0.088 3920 3.25 3.75 3.5 0.081 3483 3.75 4.25 4 0.082 3644 3.75 4.25 4 0.075 3253 4.25 4.75 4.5 0.074 3282 4.25 4.75 4.5 0.069 2965 4.75 5.25 5 0.064 2873 4.75 5.25 5 0.061 2643 5.25 5.75 5.5 0.055 2449 5.25 5.75 5.5 0.053 2309 5.75 6.25 6 0.046 2038 5.75 6.25 6 0.046 1981 6.25 6.75 6.5 0.037 1658 6.25 6.75 6.5 0.039 1670 6.75 7.25 7 0.030 1319 6.75 7.25 7 0.032 1386 7.25 7.75 7.5 0.023 1027 7.25 7.75 7.5 0.026 1133 7.75 8.25 8 0.018 784 7.75 8.25 8 0.021 912 8.25 8.75 8.5 0.013 587 8.25 8.75 8.5 0.017 724 8.75 9.25 9 0.010 431 8.75 9.25 9 0.013 568 9.25 9.75 9.5 0.007 311 9.25 9.75 9.5 0.010 439
127
9.75 10.25 10 0.005 220 9.75 10.25 10 0.008 335 10.25 10.75 10.5 0.003 153 10.25 10.75 10.5 0.006 253 10.75 11.25 11 0.002 104 10.75 11.25 11 0.004 189 11.25 11.75 11.5 0.002 70 11.25 11.75 11.5 0.003 139 11.75 12.25 12 0.001 46 11.75 12.25 12 0.002 101 12.25 12.75 12.5 0.001 30 12.25 12.75 12.5 0.002 73 12.75 13.25 13 0.000 19 12.75 13.25 13 0.001 52 13.25 13.75 13.5 0.000 12 13.25 13.75 13.5 0.001 37 13.75 14.25 14 0.000 7 13.75 14.25 14 0.001 26 14.25 14.75 14.5 0.000 5 14.25 14.75 14.5 0.000 18 14.75 15.25 15 0.000 3 14.75 15.25 15 0.000 12 15.25 15.75 15.5 0.000 2 15.25 15.75 15.5 0.000 8 15.75 16.25 16 0.000 1 15.75 16.25 16 0.000 5 16.25 16.75 16.5 0.000 1 16.25 16.75 16.5 0.000 4 16.75 17.25 17 0.000 0 16.75 17.25 17 0.000 2 17.25 17.75 17.5 0.000 0 17.25 17.75 17.5 0.000 2 17.75 18.25 18 0.000 0 17.75 18.25 18 0.000 1 18.25 18.75 18.5 0.000 0 18.25 18.75 18.5 0.000 1 18.75 18.75 19.25 19 0.000 0 19.25 19.25 19.75 19.5 0.000 0 19.75 19.75 20.25 20 0.000 0 20.25 20.25 20.75 20.5 0.000 0 20.75 20.75 21.25 21 0.000 0
Total 0.996 44444 0.994 42934 July August Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
0.25 0.75 0.5 0.040 1806 0.25 0.75 0.5 0.040 1806 0.75 1.25 1 0.059 2633 0.75 1.25 1 0.059 2633 1.25 1.75 1.5 0.070 3146 1.25 1.75 1.5 0.070 3146 1.75 2.25 2 0.077 3436 1.75 2.25 2 0.077 3436 2.25 2.75 2.5 0.080 3551 2.25 2.75 2.5 0.080 3551 2.75 3.25 3 0.079 3529 2.75 3.25 3 0.079 3529 3.25 3.75 3.5 0.076 3401 3.25 3.75 3.5 0.076 3401 3.75 4.25 4 0.072 3196 3.75 4.25 4 0.072 3196 4.25 4.75 4.5 0.066 2940 4.25 4.75 4.5 0.066 2940 4.75 5.25 5 0.059 2654 4.75 5.25 5 0.059 2654 5.25 5.75 5.5 0.053 2356 5.25 5.75 5.5 0.053 2356 5.75 6.25 6 0.046 2059 5.75 6.25 6 0.046 2059 6.25 6.75 6.5 0.040 1774 6.25 6.75 6.5 0.040 1774 6.75 7.25 7 0.034 1508 6.75 7.25 7 0.034 1508 7.25 7.75 7.5 0.028 1265 7.25 7.75 7.5 0.028 1265 7.75 8.25 8 0.024 1050 7.75 8.25 8 0.024 1050 8.25 8.75 8.5 0.019 861 8.25 8.75 8.5 0.019 861 8.75 9.25 9 0.016 698 8.75 9.25 9 0.016 698 9.25 9.75 9.5 0.013 560 9.25 9.75 9.5 0.013 560 9.75 10.25 10 0.010 445 9.75 10.25 10 0.010 445
10.25 10.75 10.5 0.008 350 10.25 10.75 10.5 0.008 350 10.75 11.25 11 0.006 273 10.75 11.25 11 0.006 273 11.25 11.75 11.5 0.005 211 11.25 11.75 11.5 0.005 211 11.75 12.25 12 0.004 161 11.75 12.25 12 0.004 161 12.25 12.75 12.5 0.003 122 12.25 12.75 12.5 0.003 122 12.75 13.25 13 0.002 92 12.75 13.25 13 0.002 92 13.25 13.75 13.5 0.002 69 13.25 13.75 13.5 0.002 69 13.75 14.25 14 0.001 51 13.75 14.25 14 0.001 51 14.25 14.75 14.5 0.001 37 14.25 14.75 14.5 0.001 37
128
14.75 15.25 15 0.001 27 14.75 15.25 15 0.001 27 15.25 15.75 15.5 0.000 20 15.25 15.75 15.5 0.000 20 15.75 16.25 16 0.000 14 15.75 16.25 16 0.000 14 16.25 16.75 16.5 0.000 10 16.25 16.75 16.5 0.000 10 16.75 17.25 17 0.000 7 16.75 17.25 17 0.000 7 17.25 17.75 17.5 0.000 5 17.25 17.75 17.5 0.000 5 17.75 18.25 18 0.000 3 17.75 18.25 18 0.000 3 18.25 18.75 18.5 0.000 2 18.25 18.75 18.5 0.000 2 18.75 19.25 19 0.000 2 18.75 19.25 19 0.000 2 19.25 19.75 19.5 0.000 1 19.25 19.75 19.5 0.000 1 19.75 20.25 20 0.000 1 19.75 20.25 20 0.000 1 20.25 20.75 20.5 0.000 1 20.25 20.75 20.5 0.000 1 20.75 21.25 21 0.000 0 20.75 21.25 21 0.000 0 21.25 21.75 21.5 0.000 0 21.25 21.75 21.5 0.000 0
Total 0.993 44322 0.993 44322 Sep Oct Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
0.25 0.75 0.5 0.025 1081 0.25 0.75 0.5 0.012 551 0.75 1.25 1 0.041 1781 0.75 1.25 1 0.026 1167 1.25 1.75 1.5 0.054 2312 1.25 1.75 1.5 0.040 1768 1.75 2.25 2 0.062 2700 1.75 2.25 2 0.052 2315 2.25 2.75 2.5 0.068 2957 2.25 2.75 2.5 0.062 2776 2.75 3.25 3 0.072 3096 2.75 3.25 3 0.070 3130 3.25 3.75 3.5 0.072 3132 3.25 3.75 3.5 0.075 3364 3.75 4.25 4 0.071 3079 3.75 4.25 4 0.078 3473 4.25 4.75 4.5 0.068 2955 4.25 4.75 4.5 0.078 3463 4.75 5.25 5 0.064 2775 4.75 5.25 5 0.075 3346 5.25 5.75 5.5 0.059 2557 5.25 5.75 5.5 0.070 3141 5.75 6.25 6 0.054 2315 5.75 6.25 6 0.064 2870 6.25 6.75 6.5 0.048 2062 6.25 6.75 6.5 0.057 2555 6.75 7.25 7 0.042 1808 6.75 7.25 7 0.050 2219 7.25 7.75 7.5 0.036 1562 7.25 7.75 7.5 0.042 1881 7.75 8.25 8 0.031 1332 7.75 8.25 8 0.035 1558 8.25 8.75 8.5 0.026 1120 8.25 8.75 8.5 0.028 1261 8.75 9.25 9 0.022 930 8.75 9.25 9 0.022 997 9.25 9.75 9.5 0.018 762 9.25 9.75 9.5 0.017 771 9.75 10.25 10 0.014 618 9.75 10.25 10 0.013 584
10.25 10.75 10.5 0.011 495 10.25 10.75 10.5 0.010 432 10.75 11.25 11 0.009 391 10.75 11.25 11 0.007 313 11.25 11.75 11.5 0.007 306 11.25 11.75 11.5 0.005 222 11.75 12.25 12 0.005 237 11.75 12.25 12 0.003 154 12.25 12.75 12.5 0.004 182 12.25 12.75 12.5 0.002 104 12.75 13.25 13 0.003 138 12.75 13.25 13 0.002 69 13.25 13.75 13.5 0.002 103 13.25 13.75 13.5 0.001 45 13.75 14.25 14 0.002 77 13.75 14.25 14 0.001 29 14.25 14.75 14.5 0.001 56 14.25 14.75 14.5 0.000 18 14.75 15.25 15 0.001 41 14.75 15.25 15 0.000 11 15.25 15.75 15.5 0.001 30 15.25 15.75 15.5 0.000 7 15.75 16.25 16 0.000 21 15.75 16.25 16 0.000 4 16.25 16.75 16.5 0.000 15 16.25 16.75 16.5 0.000 2 16.75 17.25 17 0.000 10 16.75 17.25 17 0.000 1 17.25 17.75 17.5 0.000 7 17.25 17.75 17.5 0.000 1 17.75 18.25 18 0.000 5 17.75 18.25 18 0.000 0 18.25 18.75 18.5 0.000 3 18.25 18.75 18.5 0.000 0 18.75 19.25 19 0.000 2 18.75
129
19.25 19.75 19.5 0.000 2 19.25 19.75 20.25 20 0.000 1 19.75 20.25 20.75 20.5 0.000 1 20.25 20.75 21.25 21 0.000 0 20.75 21.25 21.75 21.5 0.000 0 21.25
Total 0.997 43052 0.999 44603 Nov Dec Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
Bin Min (m/s)
Bin Max (m/s)
Mid Bin (m/s)
PDF No. of Data Points
0.25 0.75 0.5 0.004 187 0.25 0.75 0.5 0.003 141 0.75 1.25 1 0.012 529 0.75 1.25 1 0.010 430 1.25 1.75 1.5 0.022 959 1.25 1.75 1.5 0.018 819 1.75 2.25 2 0.033 1439 1.75 2.25 2 0.029 1274 2.25 2.75 2.5 0.045 1932 2.25 2.75 2.5 0.039 1763 2.75 3.25 3 0.056 2403 2.75 3.25 3 0.050 2253 3.25 3.75 3.5 0.065 2818 3.25 3.75 3.5 0.061 2709 3.75 4.25 4 0.073 3148 3.75 4.25 4 0.069 3096 4.25 4.75 4.5 0.078 3369 4.25 4.75 4.5 0.076 3386 4.75 5.25 5 0.080 3468 4.75 5.25 5 0.080 3557 5.25 5.75 5.5 0.080 3443 5.25 5.75 5.5 0.081 3599 5.75 6.25 6 0.076 3300 5.75 6.25 6 0.079 3513 6.25 6.75 6.5 0.071 3059 6.25 6.75 6.5 0.074 3310 6.75 7.25 7 0.063 2742 6.75 7.25 7 0.067 3012 7.25 7.75 7.5 0.055 2379 7.25 7.75 7.5 0.059 2648 7.75 8.25 8 0.046 1997 7.75 8.25 8 0.050 2249 8.25 8.75 8.5 0.038 1622 8.25 8.75 8.5 0.041 1844 8.75 9.25 9 0.030 1275 8.75 9.25 9 0.033 1460 9.25 9.75 9.5 0.022 969 9.25 9.75 9.5 0.025 1115 9.75 10.25 10 0.016 713 9.75 10.25 10 0.018 821
10.25 10.75 10.5 0.012 506 10.25 10.75 10.5 0.013 583 10.75 11.25 11 0.008 348 10.75 11.25 11 0.009 399 11.25 11.75 11.5 0.005 230 11.25 11.75 11.5 0.006 263 11.75 12.25 12 0.003 147 11.75 12.25 12 0.004 166 12.25 12.75 12.5 0.002 91 12.25 12.75 12.5 0.002 101 12.75 13.25 13 0.001 54 12.75 13.25 13 0.001 59 13.25 13.75 13.5 0.001 31 13.25 13.75 13.5 0.001 33 13.75 14.25 14 0.000 17 13.75 14.25 14 0.000 18 14.25 14.75 14.5 0.000 9 14.25 14.75 14.5 0.000 9 14.75 15.25 15 0.000 5 14.75 15.25 15 0.000 5 15.25 15.75 15.5 0.000 2 15.25 15.75 15.5 0.000 2 15.75 16.25 16 0.000 1 15.75 16.25 16 0.000 1 16.25 16.75 16.5 0.000 0 16.25 16.75 16.5 0.000 0 16.75 17.25 17 0.000 0 16.75 17.25 17 0.000 0 17.25 17.75 17.5 0.000 0 17.25 17.75 17.5 0.000 0 17.75 18.25 18 0.000 0 17.75 18.25 18 0.000 0 18.25 18.75 18.5 0.000 0 18.25 18.75 18.5 0.000 0
Total 1.000 43195 1.000 44638
130
D6 Buildings with their Respective Heights Located at Jandakot Airport Figure next page
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132
D7 Roughness Values Suggested by the European Wind Atlas Based on Characteristic of the Terrain Type
Figure 43 Roughness values suggested by the European Wind Atlas based on characteristic of the terrain type (Petersen et al., 1989)
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Appendix E Bench Testing
E1. Data logger Program for the Monitoring Equipments During Bench Test 'JOB=JOB1 'COMPILED=2010/02/22 12:43:51 'TYPE=dt80 DT=\d BEGIN"JOB1" CATTN 'Spans and polynomial declarations Y1=0.3278,0.1007"m/s" Y2=0.24665,0.62421"m/s" S3=-40,60,0,2.5"C" S4=0,100,0,2.5"%RH" Y5=10.62,21.79"kPa" S6=0,360,0,12"Deg" 'Thermistor declarations 'Switches declarations 'Parameter declarations 'Global declarations RS1S 'schedule definition RA"TEST"("B:",ALARMS:OV:100KB,DATA:NOV:25MB)1S LOGONA GA 1*HV(=6CV) 1+HV(=7CV) 3HV(S6,"Direction") 9CV(S3,"temperature")=6cv 8CV(S4,"humidity")=7cv 2HV(=10CV) 11CV(Y5,"pressure")=10cv 3HSC(R,=1CV,AV) 4HSC(R,=2CV,AV) 3HV 3CV(Y2,"P2546A")=1cv 4CV(Y1,"viasala")=2cv END 'end of program file
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E2. Graphs of Sensor Recordings During the Bench Test
Figure 44 Bench test results for the 2 cup anemometer P2546A and WAA151
Both the anemometer RISOP2546A and Vaisala WAA151 shows reading similar to
each other.
135
Figure 45 Bench test results for temperature, relative humidity, barometric pressure and wind direction sensor
Temperature, relative humidity, barometric pressure and wind direction sensor
recorded realistic measurements during the be