currie community high school energy audit report - eca sites
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Currie Community High School Energy audit report
David Jenkins1, Gillian Menzies
1, Richard Kilpatrick
1, and Tessa Parnell
2
1 Urban Energy Research Group, School of Built Environment, Heriot-Watt University, Edinburgh
2 Mott-MacDonald Fulcrum, London
1. Introduction
This report is an overview of the energy consumption and behaviour of Currie Community High
School (CCHS), as part of a UK Energy Research Centre/NESTA funded study “Measuring Climate
Change Good Practice in Schools”. This overview is intended to inform the wider study, which
investigates the effect of an exemplary low energy school within a local community.
CCHS was built in the mid-1960s with a series of refurbishments carried out in the 1990s. The
school have recently invested in a small-scale wind turbine and solar thermal installation, the
latter used to heat the swimming pool (though these post-date the energy data used in this
report). The primary form of space and water heating is mains gas and other services (IT, cooking
etc) are typical of a modern secondary school. Low energy lighting, such as compact and tubular
fluorescent, is prevalent throughout the building, though there are aspects to the construction
of the building that are less efficient – and this is typical of the building construction age.
The school also has a well-established sustainability ethic, which influences their teaching and
public outreach programmes. Like many schools in built-up areas, the building is also used for
evening classes and other extra-curricular activities.
The work described in this report is being led by University of Leeds, with Heriot-Watt University
managing the energy consumption data analysis overviewed in this report. Canterbury Christ
Church University and Mott MacDonald are also involved as project partners. This energy report
will aim to analyse the available energy data and draw comparisons with other schools and
industry benchmarks.
2. Annual and monthly energy consumption patterns
Energy consumption data was provided by the school at different intervals. Electrical demand
data was available in the form of half-hourly measurements, while monthly gas bill data (for
heating and hot water) was also provided. While the temporal detail in the electrical demand
data will be explored in later sections, to highlight year-on-year changes to the energy patterns
of the school the monthly data for both electrical and gas consumption will now be examined.
2.1 Boiler consumption data
Data for heating and boiler usage can be collected in two ways. A more hi-tech approach, and
only relevant for long-term studies, would be to use monitoring equipment that directly records,
in this case, the gas usage. One way of doing this is to measure the temperature of the incoming
and outgoing water in the central heating system, while simultaneously measuring the flow rate
of this water (through, for example, an ultrasonic flow detector). The result of these
measurements is enough to calculate the energy being consumed to heat this flow of water,
which is essentially the energy being consumed by the boiler.
A more straightforward approach is simply to use gas bill data as a record of energy
consumption. An example of such data is given in Figure 1. The weakness of using this data for
an energy analysis is immediately clear. As bill data will usually be a result of paying an account
with the energy supplier, which can be in debit or credit at any given time, it is often a poor
indicator of real energy consumption over a given month.
Further to this, the tariff used year-on-year is subject to fluctuations. Therefore, from Figure 1
alone, it is not possible to ascertain whether, for example, 2006 was a particularly cold year or
the energy tariff just happened to be substantially more. From the provided data, the tariffs in
use (averaged over each year) are 1.31, 1.86 and 2.63p/kWh for 2004, 2005 and 2006
respectively. Assuming these are reasonably consistent over each year, and ignoring standing
charges, the corresponding estimated gas consumption values are given in Figure 2.
Figure 1 – Monthly gas bill data (£) of CCHS for 2004-2006
£0
£2,000
£4,000
£6,000
£8,000
£10,000
£12,000
£14,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Gas
bill
(£
)
2004
2005
2006
Figure 2 – Monthly gas consumption estimates (MWh) of CCHS for 2004-2006
After applying the different tariffs, there is less year-on-year variation. The annual gas
consumption using these estimates is 3,159, 2,368 and 2,768 MWh respectively for 2004, 2005
and 2006. However, it is also clear from both Figures 1 and 2 that, for example, a high December
bill is followed by a low January bill and vice versa (a low December bill followed by a high
January bill). This is likely to be a result of the debit/credit problem of using gas bill data to
estimate consumption.
A useful compromise between measuring this data and reading gas bills would be for a member
of staff to record the actual meter reading once a month. This will provide the school with real
energy data and identify when energy is being used and how it might relate to changes occurring
in the school over time. This would enable firmer conclusions to be made from such data.
2.2 Electrical consumption data
Figure 3 presents the monthly electrical consumption for CCHS, for 2006, 2007 and 2008 – note
that these are different years to those used for the gas consumption analysis due to the data
available at time of writing. A similar month-on-month trend is seen for all three years, with
reduced electrical consumption during the warmer months, though variations in these trends
are subject to similar issue as discussed in section 2.1 (such as the effect of term times).
0
100
200
300
400
500
600
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Esti
mat
ed
gas
co
nsu
mp
tio
n (
MW
h)
2004
2005
2006
Figure 3 – Monthly electrical consumption estimates (MWh) of CCHS for 2004-2006
The total annual electrical energy consumption from this data is 612, 625 and 584MWh for 2006,
2007 and 2008 respectively. This year-on-year variation is relatively modest, though the total
electrical energy consumption in 2008 is 7% less than that of 2007. With local, historical weather
information (not available for this report) it would be possible to further investigate if the
variations observed can be explained from climate effects alone, or whether additional changes
to the building or user behaviour are affecting the energy consumption. Section 3 further
explores this electrical demand data at a higher temporal resolution.
3. Electrical demand profiles
When attempting to investigate energy patterns in a building, annual or monthly energy
consumption data does not usually provide sufficient detail. With the hourly data supplied by
CCHS, the pattern of energy consumption throughout a day, and how this might change by
season, can be displayed and the reasons for variations postulated.
Figure 4 shows average daily profiles for the three years where electrical consumption data was
available (2006, 2007 and 2008). The very similar patterns seen year-on-year are a result of the
averaging process – if every weekday is averaged together across an entire year then the effect
is to smooth out the profile shape into something that could be describe as generic. While 2006
and 2007 are very similar in magnitude, 2008 shows a noticeable reduction in energy use,
particularly during peak times (that will correspond to times of highest occupancy). It is
suggested that this could be due to lighting upgrades over this time, though reductions in space
heating (due to draughtproofing, insulation measures or simply a warmer winter) can also have
0
10
20
30
40
50
60
70
80
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Ene
rgy
(MW
h)
Month
2006
2007
2008
a noticeable effect – with the gas boiler used less, the electrical consumption associated with the
delivery of this heat will be reduced.
Figure 4 – Average weekday electrical consumption profiles for 2006, 2007 and 2008 in CCHS
Figure 5 – Comparison of daily electrical consumption profiles for CCHS during 2008
0
20
40
60
80
100
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Po
we
r (k
W)
Time
2006 Weekday
2007 Weekday
2008 weekday0
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Po
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200-250
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0-50
To encapsulate variations in electrical usage throughout a day and throughout the year
simultaneously, Figure 5 shows 365 daily electrical profiles for 2008. Term times can be clearly
seen (e.g. during the summer) but also the gradual change in profile shape during the year.
There is a very strong correlation with climate – January is typically the coldest month and this
period is where the highest electrical usage (over 200kW peak power recorded) is observed. This
implies that the electrical consumption of the pumps and fans associated with the gas boiler,
along with lighting usage during times of poor daylight, are having an influence on this electrical
consumption.
4. Comparisons with other schools
When attempting to assess the real energy performance of a school there are two particularly
useful comparisons to carry out, namely: (i) the energy consumption of the school when
compared to benchmark data and (ii) the energy consumption of the school when compared to
other schools. The sections below carry out these comparisons, where data exists.
4.1 Benchmark data
The electrical energy consumption data for 2008 for CCHS is 584MWh/yr, equating to
49kWh/m2. The gas consumption data for 2006 (most recent available at time of writing) has
been estimated (from section 2.1) at 2768MWh or 232kWh/m2.
Table 1 is a list of currently available benchmarks that are sometimes referred to in the building
design industry. At first glance, CCHS appears to be slightly higher than “typical” in both gas and
electricity usage; however, there are several caveats that should be borne in mind before
making conclusions from this table. Firstly, CCHS is in Scotland, whereas the benchmarks are UK-
wide – a Scottish school would be expected to have a significantly higher energy consumption
than those in southern UK.
Table 1 – School gas and electricity consumption benchmarks used in industry
Gas consumption
(kWh/m²/yr)
Electricity consumption
(kWh/m²/yr)
Source
Benchmark Typical practice
Good practice
Typical practice
Good practice
Secondary Schools 174 136 30 24 ECG 731
Secondary Schools (no pool)
157 110 34 25 GPG 3432
Secondary Schools (with pool)
187 142 36 29 GPG 343
Secondary Schools – 50th percentile
155 n/a 39 n/a E&WBE3
Secondary Schools – 25th percentile
n/a 112 n/a 31 E&WBE
Secondary schools, NI
120 101 22 16 EBPSBNI4
CCHS 232 49
Just as importantly, the energy benchmarks of Table 1 are not based on recent assessments of
school energy consumption – and even some of the provided references disagree as to what is
“typical” and “good practice” energy use in the schools sector. In addition to this, the PPP and
PFI schools projects that have been underway over recent years (though now largely finished),
along with a rapid increase in IT energy consumption, has changed school energy patterns.
These uncertainties highlight the importance of real energy data, and also comparing like with
like. With this in mind, section 4.2 takes some real energy data of a selection of Edinburgh
schools and investigates the performance of CCHS in this context.
4.2 Data from other schools
As part of a PhD project at Heriot-Watt, the electrical consumption of several Edinburgh schools
are currently being collated. The results are shown in Table 2 and Figure 6, with CCHS
highlighted (all other schools are anonymous). It should be noted that electrical consumption
alone is not sufficient for a complete comparison of energy consumption between schools, but
gas consumption data was not available for these other schools (and is generally more difficult
to obtain). However, total electrical consumption can be a useful indicator of overall energy
management in the school as low figures will generally only be possible if a concerted effort is
made with regards to, for example, switching off lighting and IT equipment.
1 Energy Consumption Guide 73: Saving Energy in Schools, Energy Efficiency Best Practice Programme, 1996
2 Good Practice Guide 343: Saving Energy – a Whole School Approach, Carbon Trust, 2005
3 Energy and Water Benchmarks for Maintained Schools in England: 2002-03, DfES
4 Energy Benchmarks for Public Sector Buildings in Northern Ireland, Jones, Turner, Browne, Illingworth,
Proceedings of CIBSE National Conference Dublin, 2000
Table 2 – Edinburgh schools data from Heriot-Watt University project (originally supplied by City of
Edinburgh Council)
*CCHS
+Recently undergone refurbishments
Figure 6 – Electrical consumption per unit floor area for selected Edinburgh schools (CCHS in red)
School AgePrimary/
Secondary
Floor
Area (m²)
No. of
Pupils
Annual
Electricity
use (MWh)
Swimming
Pool
Energy Per
floor area
(kWh/m²)
Energy Per
Pupil
(kWh/pup)
A 1983 S 8042 782 667 P 83.0 853
B 1978 P 4082 389 225 - 55.1 579
C 2009 S 16852 933 966 P 57.3 1035
D 1960 P 2535 174 195 - 77.0 1122
E 1980 S 9382 275 343 - 36.5 1245
F 1989 S 11430 1102 513 P 44.9 465
G 2008 S 1120 59 240 - 214.0 4061
H 1968 P 4001 395 134 - 33.5 340
I 1975 P 4111 367 219 - 53.2 596
J 1966 S 2316 101 147 - 63.6 1459
K 1991 S 12349 923 863 - 69.9 935
L 1954 P 13145 712 441 P 33.6 619
M 1895 P 6162 240 389 - 63.1 1621
N 1961 P 2515 290 487 193.5 1678
O 1960 S 15368 1423 695 P 45.2 489
P 1970 S 11535 806 644 - 55.8 799
Q 1964 S 1405 55 299 212.8 5437
R 2002 S 9168 744 598 P 65.2 804
S 1893+ S 11742 913 565 P 48.1 619
T 1978 S 11436 401 1433 P 125.3 3574
U 1970 S 2304 78 71 30.7 907
V* 1965 S 11918 902 584 P 49.0 648
W 2007 P 2700 260 162 - 59.9 622
X 1937 P 2800 399 176 - 62.8 440
0
50
100
150
200
250
G Q N T A D K R J M X W C P B I V* S O F E L H U
Elec
tric
al c
on
sum
pti
on
(kW
h/m
2)
School
Figure 6 shows that the electrical consumption of CCHS, at 49kWh/m2, is towards the lower end
of the school energy data used in this comparison. This level of energy consumption appears
consistent with a low energy school. Furthermore, the other secondary schools built in the 1960s
and 1970s (labelled J, O, P, Q, T and U) are quite diverse in terms of electrical energy use, though
only O and U have lower consumption figures than CCHS, with U not having a swimming pool.
Therefore by most real comparisons CCHS performs well, particularly for the type of building
that the school operates from. The comparison with energy benchmarks is less clear, though
such benchmarks are often poor indicators of real energy use and should be used with caution.
5. Improving the energy efficiency of the school
Schools account for 2% of UK carbon emissions, equivalent to 15% of UK public sector
emissions.5 The government’s carbon management strategy for the schools sector, published in
April 2010, sets an ambitious target to cut emissions from energy use in schools by 53% by 2020.
This needs to be tackled through a number of complimentary strategies: investment in
upgrading the fabric of school buildings, and investment in technological interventions, together
with conscious user behaviour changes. Schools are the ideal teaching grounds for energy
efficiency and investment projects. Energy efficiency has been introduced into the curriculum
with the aim that educating young people in sustainable practices, from an early age, will help
embed behaviour change and lead to a more sustainable society.
According to IMserv6 and their report on Energy Savvy Schools there are five challenges to
energy saving in schools:
• Complete and accurate energy-related data
Smart metering enables remote, automated and accurate half hourly reading of energy
usage on a building(s) basis. To understand where, when and how energy is being used
requires consumption to be identified from specific sources such as heating, lighting and ICT.
This can be achieved by installing sub-meters for different locations, even specific rooms and
devices if necessary. Sub-metering may help identify energy usage for community or after
hours activities; use of zoned controls would allow only the areas required to be supplied
rather than heating the whole school for a single event. CCHS already has access to half-
hourly electrical consumption data, but as shown above, data pertaining to gas consumption
is often estimated, on a per-school basis, and links only roughly to weather data and
occupation. More frequently sampled and zoned data would help identify specific heating
and hot water energy consumption, and encourage behavioural changes to reduce
consumption.
Energy, environmental and financial benefits derived through efficiency
improvements are immediate. Solar panels, in contrast, typically take three
5 Climate Change and Schools: a carbon management strategy for the school sector, Department for Children,
Schools and Families, DCSF-00366-2010. 6 Creating the Energy Savvy Schools of Tomorrow, IMSERV White paper, available at
www.imserv.com/energy-savvy-schools
years before they ‘pay back’ the carbon emissions embedded in their
manufacture, and 10 years before they yield a true financial return – even
with generous government subsidies.7
• Limited or no specialist experience in interpreting energy and related data
Energy conservation requires specialist expertise to transform raw energy data into
actionable ‘energy intelligence.’ CCHS is somewhat fortunate to have a Business Manager in
place, whereas other schools may rely on teaching staff to ‘champion’ energy management
on top of their academic duties. Effective and ongoing energy saving is achieved through
monitoring of day-to-day energy consumption. Analysis of real energy consumption and
patterns can identify sources of waste, leading to behavioural and operational changes
which deliver carbon and monetary savings. Having complete and reliable energy data
means that schools can be in a better position to negotiate more attractive tariffs with
suppliers.
• Problems in making energy insight and savings visible to all
Feedback is important in reducing energy consumption. CCHS already provide a large display
screen in the school reception area visually showing in real-time, staff, pupils and visitors the
positive contribution which the 11kW wind turbine and 30kW solar thermal installations
make. Solar panels and wind turbines may not enjoy the same financial or environmental
benefits as energy efficiency but do have the advantage of being visible and engaging,
especially for young people.
• Difficulty embedding change and accurately monitoring progress
The need to continually monitor energy consumption and behaviour is emphasised: changes
to the working environment, fluctuations in energy prices, building use changes, new targets
and new technologies all affect the decision making process in reducing energy
consumption.
• Not taking a ‘whole school’ holistic approach
Having an ‘Energy Champion’ or business manager will reap benefits more effectively and
quickly. Sustained change will result from involving the whole school in a cross-curriculum
manner, and allowing pupils to understand how energy efficiency and supply affects, and is
affected by, economics, technology, media, and natural resources. The analysis of data can
be considered from a scientific and mathematical stance, and critiqued through use of
language and interpretation. CCHS is making good educational use of the data throughout a
number of its core curriculums and at various levels throughout the school.
CCHS are using the resources they have to good effect with good visibility of installed
technologies and embedded curriculum use of data and sustainable development issues. The
school building itself would benefit from a number of technological improvements which would
impact significantly on gas consumption for space heating and electrical loads for lighting and
equipment. Technological improvements include:
7 Creating the Energy Savvy Schools of Tomorrow, IMSERV White paper, Page 2.
Lighting
Lights left on in one room during break, lunch and after school for one academic year costs an
additional £117 in electricity8. Behavioural campaigns to remind occupants to switch lights off can
be effective, but need constant reminders and feedback to provide lasting benefits.
Lighting controlled by occupancy sensors, photocell sensors, daylight-linked dimmers and time
controls can have relatively short payback periods, ranging from 2-10 years9. This period of
payback is dependent upon a baseline which is determined by the existing technology efficiency,
the hours of use, and the controls which are employed. Areas which can take advantage of
natural daylighting should be separately controlled.
LED lighting offers the potential to significantly reduced energy consumption. Some designs of
LED luminaries offer very directional light quality, rather than diffusing light over a large space.
This may mean that LED’s are still not ideal for large spaces requiring uniform light distribution
levels (e.g. a classroom), but are more suited to spotlight applications e.g. countertops and
display areas. However, both this problem and the high cost factor of LED lighting (a previous
barrier) are improving year-on-year, and this technology is likely to become a more common
lighting choice in buildings in the near future. More commonly used is low energy fluorescent
tube lighting, which can have payback periods as low as 2-3 years.9
Heating
The first rule in reducing energy consumption in buildings is to reduce demand, and then to
provide the required energy as efficiently as possible. To reduce demand in CCHS requires simple
and low-tech solutions like wall and roof insulation, draughtproofing, or window replacement,
with paybacks as listed below 9. [Note – upgrading well fitting single-glazing to double-glazing or
advanced passive glazing options can take over 13 years to pay back in financial terms, based on
electrical heat supply, and up to 50 years based on gas heat supplies. As energy prices rise, this
payback period will naturally fall, but will remain significant in the short to medium term10.]
Wall insulation payback 3-6 years
Roof insulation payback 2-4 years
Draughtproofing payback 1-3 years
Condensing energy efficient boilers have significantly higher efficiencies than standard non-
condensing boilers (>87% efficiency compared to 75% or less). Condensing boilers extract heat
from otherwise wasted flue gases. Instead of a single pass heat exchange system which expels
flue gases at 180°C, condensing boilers reroute these gases over a second heat exchanger and
8 Currie Community High School website, http://www.curriechs.co.uk/
9 Good Practice Guide 312, Pages 23-25 Invest to save?: financial appraisal of energy efficiency measures
across the government estate, available from www.carbontrust.co.uk 10
Menzies, G. 2010 Carbon, Energy and Monetary Investment Model for Low Carbon Building Design, International Renewable Energy Conference, Sousse, Tunisia, 5-7 November.
expel at around 55°C. Payback periods of around 2 years are quoted11. It is stressed that payback
periods are heavily subject to existing systems, patterns of use and replacement options.
Equipment changes
Use of ICT equipment in schools is consistently increasing with the use of smart boards and
increased use of PCs. These technologies not only consume large quantities of power, but they
also emit a significant amount of heat. This heat poses a significant threat to overheating in
schools12. Use of low energy (15W) laptops has a combined effect of lowering electricity
consumption and emitted heat.
Low and Zero Carbon Technologies (LZCTs)
The use of LZCTs should only usually be considered after demand-reduction measures have been
considered. Reducing demand is generally a more cost-effective approach, and can also change
the types of LZCTs that might be effective. Table 3 presents the capital and running costs,
payback periods and carbon reduction potential of selected carbon saving technologies – though
these are not building-specific carbon-savings, merely indicative savings from literature13.
Some of these measures, much like the LZCTs already installed in CCHS, are visible and therefore
can have additional value for a building such as a school – but this should not be used to over-
estimate their significance when compared to some of the previously suggested energy efficiency
improvements.
Table 3 –carbon savings and payback periods of chosen LZCTs
Capital cost per kW
Running costs Payback time Lifetime CO
2
reduction per £
Solar thermal systems Low-Medium Low Low-Medium High
Photovoltaics High Low High Medium
District Heating Medium-High Low Medium-High Medium-High
Combined Heat and Power
Medium Low-medium Medium High
Ground source heat pumps
Medium Low Low-Medium High
Wind power Medium-High Low Low-Medium High
Biomass Medium Low-Medium Medium Medium-High
11 CT021 Carbon Trust, How to implement condensing boilers, available from www.carbontrust.co.uk
12 Jenkins D.P., Peacock A.D. and Banfill P.F.G., Will future low-carbon schools in the UK have an overheating
problem?, Building and Environment, 44, 2009, 490-501 13
Shearer, D and Anderson, B, SBSA, 2005, Low and Zero Carbon Technologies in the Scottish Building Standards
6. Conclusions
Currie Community High School has a clear objective to teach and practice sustainability and
energy efficiency, and this is reflected in the recorded energy consumption. From the data
available, the school is near the lower end of school energy use when compared to a database of
Scottish schools. Due to the age of the building, it is likely that a considerable contribution to this
energy efficiency emanates from good energy behaviour – i.e. despite the construction of the
building not being exemplary, the energy practices carried out within the building appear to be
successful.
Comparing the school to energy benchmarks, much of which is based on outdated energy data,
places the school in a more average setting – but, as already discussed, it is suggested that this is
more about the veracity of the generic energy benchmarks, rather than the energy efficiency of
CCHS.
A list of typical energy improvements have been provided that CCHS might look at adopting in the
future. Before carrying out such measures, a more detailed investigation of the building itself
would need to be carried out, but this report could be used to aid such an objective.
19th May 2011