integrating wind generation into the grid -- a...
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Integrating Wind Generation into the Grid -- A Primer
Authors: Rich Lauckhart, with Steve Balser, Jeffrey R. Dykstra, Ryan Pletka, Tim Mason,
Ric O’Connell, Dennis Noll, Roger Schiffman, Mark Griffith, Natalie Rolph, Mike Elenbaas Enterprise Management Solutions Division
September 2009
Integrating Wind Generation to the Grid – A Primer
September 2009 Black & Veatch Corporation
TABLE OF CONTENTS Definition of Wind Integration Cost................................................................................................................... 1
Operational Timeframe Issues in the Power Industry ........................................................................................ 3
Reliability Criteria Relating to Frequency Control – Matching Loads and Resources ...................................... 6
Evaluating the Cost of Wind Integration............................................................................................................ 8
Impacts on Resource Adequacy When Wind Is Included in the Supply Portfolio........................................... 16
Methods to Mitigate the Cost of Integrating Large Amounts of Wind ............................................................ 19
Insights Gained From Large Control Areas Regarding Wind Integration........................................................ 21
Summary of Wind Integration Issues ............................................................................................................... 22
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he issue of integrating wind resources into the power grid needs to be discussed in the context of
how utilities have dealt with the uncertainties of matching load and generation since the birth of
the industry more than a century ago.
T
There is a need to forecast wind generation. All else being equal, the better that the wind can be forecast
(day-ahead, hour-ahead, next 10 minutes) the easier it will be for system operators to line up the
resources to accommodate the expected changing wind output, and there will be less need to modify the
plan in real time.
Development of wind generation forecasting science and technology has been underway for several
years. As the utility industry gains operating experience with wind, it appears to be getting better at
forecasting the wind. The integration of adaptive techniques that allow system operators to anticipate or
modify pre-scheduled wind generation based on real-time weather data is a key to reducing wind
integration costs.
The fact remains that even if accurately forecast, the wind will vary from hour to hour. Further, the
forecasts will never be completely accurate for every 10-minute period. There will be a need to deal with
these fluctuations. Therefore, efforts are underway to study the cost of dealing with these fluctuations,
that is, the cost of integrating the wind.
Definition of Wind Integration Cost Every element of any power system is included in what is known as a “control area.” Power supply
(generation) and demand (load) are always supposed to be balanced, or matched, by the control area
operators, both within each area and through the connections to other control areas. Wind “integration
cost” describes the financial impact of the variability of the wind on the control area is to receive that
power. The financial impact is normally measured with respect to two time horizons:
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1. Short-term planning to match resources with demand over the coming day (or days) and coming hour. This involves:
• Estimating the hourly output of wind generation over the 24 hours of the next day and committing and scheduling non-wind resources that will be needed to meet the remaining demand after taking into account hourly load and wind patterns.
• Updating the estimate of the power demand and wind-generated output over the next
hour and modifying the schedule for non-wind resources to balance the new estimated demand and supply for the upcoming hour.
2. Operational time frame, comprising the real-time management of conventional generating units with wind generators.1 This includes:
• Moment-to-moment changes that need to be handled by automatic generation control/regulating reserves. Typically, this aspect of wind integration cost is evaluated by examining 10-minute (or less) anticipated wind output data to determine how that variability affects the ability of the control area operator to meet its reliability obligations.
• Operator-initiated changes in the output of non-wind resources to offset trends in wind
output within an hour.
Typically, the incremental transmission infrastructure needed to integrate wind generation is not
considered a wind integration cost, although there is often a need for new transmission in order to move
the output of new wind plants without creating undue congestion on the grid.
Also, the additional supply needed to assure that the nameplate capacity of the wind plants can be fully
counted for resource adequacy purposes – the planning reserve margin -- is not considered a wind
“integration” cost. However, the contribution of a wind plant to resource adequacy can provide
additional value to the purchaser of the plant’s output. Different utilities in the Southwest, for example,
will count the resource adequacy contribution from wind in a range from near zero to approximately
25% of the full capacity of the plant. It is common to use an effective load-carrying capability study to
1 Industry solutions already in place to cover unanticipated load or generation swings, such as spinning reserves and quick start reserves, will also be available to help with wind fluctuations. One question to be answered is, will the amount of these contingency reserves need to be increased should significant amounts of wind generation be added to the system?
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determine the effective capacity value of a particular wind facility. This is discussed in greater detail
later.
Operational Timeframe Issues in the Power Industry From the earliest days of the power industry in the late 1800s, power system operators needed to deal
with uncertainty in the load and therefore uncertainty in the amount of power that would need to be
served in the next day, hour and minute. If load and generation did not exactly match, the power
frequency of the system would vary from the target frequency – the United States utility grid operates on
a frequency of 60 cycles per second. If there is too much generation, the system frequency increases; too
little and it decreases. Either one can damage motors, appliances, and other equipment. In the early days
the primary need to control the frequency was simply to avoid damaging electric devices, although small
shifts in frequency are generally harmless.
With the invention of the synchronous motor electric clock in the 1920s, power system frequency began
to be used for timekeeping accuracy. Network operators will regulate the daily average frequency so that
clocks stay within a few seconds of the correct time. If the frequency is on the high side for a period of
the day, operators will intentionally reduce the frequency for other periods of the day so that electric
clocks will provide reasonably accurate time. Frequency variations can also cause some lighting
technologies to noticeably flicker.
If frequency decreases too much, however, most power distribution systems will disconnect blocks of
load to prevent cascading outages.
In the steady state, the frequency across a grid connected with alternating current transmission lines is
identical in all areas of the grid. Generators must all operate at the same speed in order for transmission
lines to avoid tripping due to overload.
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mall shifts in frequency do not degrade reliability or market efficiency, although large changes can
damage equipment, degrade end-use performance, and interfere with system protection protocols
which may ultimately lead to system collapse. As can be seen from Figure 1, systems are designed to
allow frequency in the range of 59 to 61.5 cycles before more extreme actions will be taken.2 The
amount of frequency change that will occur for any imbalance amount is a function of the inertia of the
generators in operation as well as the amount of time that passes before adjustments are made to remedy
the imbalance.
S
It is not possible or desirable to require tight frequency control on the power grid; it is not necessary to
require load and generation to exactly match at all times. Still, there is a need to control frequency (and
thus balance load with resources) within certain tolerance levels. The power industry has developed
mechanisms and automated controls to accomplish this. Automatic generation control (AGC) is a
computer-based control system that matches schedules with generation output every six seconds or less.
The AGC sends signals to power plants to adjust their output to counteract the variations from the
schedules.3 The utility industry does not expect that AGC controls will match generation with load at all
times. If AGC cannot keep the frequency within a small variation from the target 60 Hertz, then
governor controls on the power plants will sense the speed of the generator -- the frequency of the
system -- and are designed to counteract frequency excursions.
If these steps are not sufficient to keep the frequency within acceptable ranges, then more drastic system
protection controls are activated to avoid equipment damage. System protection controls will
automatically trip generation if frequency gets too high (if generation is greatly exceeding load). System
protection control will drop pre-designated load if frequency gets too low (load is greatly exceeding
generation). The rate at which frequency moves depends upon the magnitude of the energy imbalance
and the inertia of all of the generators and loads within the system. Figure 1, which appeared in a 2002
2 The frequency would not normally vary nearly this much, but this much variation is possible. 3 The AGC control signal will generally reflect both the difference in scheduled vs actual interchange as well as the then occurring frequency on the grid.
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paper prepared for the California Energy Commission, shows the nested structure of the frequency
control, protection and equipment damage limits.4
Figure 1
Frequency Ranges and Control Elements
When governor controls act to bring loads and resources back toward balance, it is likely that the load
for one party is being served by generation of another party, through which service has not been
contractually arranged. When this happens, “imbalances” are said to have occurred. For commercial
purposes, it is necessary to settle up these imbalance energy amounts from time to time.
4 “Frequency Control Concerns in the North American Electric Power System,” December 2002, ORNL/TM-2003/41
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Reliability Criteria Relating to Frequency Control – Matching Loads and Resources
While loads and resources do not need to be exactly matched at all times, it is important that acceptable
performance standards be set for frequency control. Establishing these operational limits has proven to
be difficult. Balancing authorities across the interconnect rely on each other for mutual support in the
event a balancing authority has a temporary load/generation imbalance. This mutual reliance, without
charge, allows the systems to support each other and reduces overall costs of providing power service in
the entire interconnect.
The Federal Energy Regulatory Commission (FERC) has been assigned by Congress to develop
mandatory reliability criteria for the power industry. With regards to matching loads and resources,
FERC has developed Control Performance Standards, another term for reliability requirements, also
known as CPS1 and CPS2, and assigned the responsibility for meeting those to balancing authorities, or
control areas. The more difficult standard to meet is CPS2 which states as follows:
Each Balancing Authority shall operate such that its average ACE5 for at least 90% of clock-10-minute periods (6 non-overlapping periods per hour) during a calendar month is within a specific limit, referred to as L10.
5 Area Control Error (ACE) is the difference between scheduled and actual electrical generation within a control area on the power grid, taking frequency bias into account. To elaborate, generating an amount of electricity in exact equilibrium with consumption (load), is extremely difficult and also quite impractical. Instead, generation controllers strive to continually alternate between over- and under-generating. The formula for calculation of ACE follows:
ACE = (NIA - NIS) - 10b (FA - FS) Tob + IME
Where:
• NIA represents actual net interchange (MWs). • NIS represents scheduled net interchange (MWs). • b represents the control area's frequency bias setting (MW/0.1 Hz). • FA represents actual system frequency (Hz). • FS represents scheduled system frequency (60.0 Hz in North America). • Tob represents scheduled interchange energy used to bilaterally correct inadver10t accumulations (MWs). • IME represents a manually entered amount to compensate for known equipment error (MWs).
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ssu
me
If the load forecast is right on target and the supplies behave as reflected in the pre-schedule, then the
flow on these lines will exactly equal the scheduled flows. However, if something happens such that the
load or supplies vary from forecast, then the utility has regulating reserves available -- additional power
supplies that can be ramped up or down very quickly -- to automatically adjust the generation to assure
the flows on the lines match the schedule. If the regulating reserve resources are unable to perfectly
adjust, then there is a deviation from the schedule.
me for purposes of this discussion that L10 for a particular balancing authority is 24
gawatts (MW). For that balancing authority, monthly CPS2 violations occur if more than 10%
of the 10-minute periods in the month demonstrate a flow on tie lines that are more than 24 MW above
or below scheduled flows. In other words, the utility develops a schedule of the specific resources it has
arranged to meet its control area forecast load. That schedule may reflect either imports into its control
area or exports from its control area. The lines that can move power into and out of the control area are
constantly monitored.
A
A CPS2 violation will occur in one of the 10-minute time slices of the month if the variation of actual
flow over the ties varies from the scheduled flow by more than a 24-MW average over the 10 minute
period. If fewer than 10% of the 10 minute intervals in a month show deviations from schedule to be less
than the 24 MW limit, then there are no violations of the FERC CPS2 reliability criteria. In other words,
a single 10-minute CPS2 violation does not violate the FERC reliability criteria. Only if more than 10%
of the 10-minute intervals in a month are outside the 24 MW limit is there a violation of the FERC CPS2
reliability criteria. FERC has established levels of severity of violations. For CPS2 criteria, a monthly
CPS2 violation falls into one of four categories:
Level 1: One instance during a calendar month in which the control area’s value of CPS2 is less than 90% but greater than or equal to 85%.6
6 Note, when reading these severity levels, 90% means that 10% of the 10-minute intervals have failed and 90% have not failed. So severity level one, between 90% and 85% means that between 10% and 15% of the 10-minute intervals have failed.
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Level 2: One instance during a calendar month in which the Control Area’s value of CPS2 is less than 85% but greater than or equal to 80%.
Level 3: One instance during a calendar month in which the Control Area’s value of CPS2 is less
than 80% but greater than or equal to 75%. Level 4: One instance during a calendar month in which the Control Area’s value of CPS2 is less
than 75%. Evaluating the Cost of Wind Integration
Evaluating the “Cost” of Day-Ahead Expected Hourly Wind Patterns -- Clearly wind generation will
not be the same in every hour of the year, month, or day. Wind data will generally show an
average/expected hourly wind pattern that varies from season to season. This hourly variation may be
helpful or problematic depending on how the expected hourly wind generation pattern matches up with
expected hourly load patterns. A graphic of an hourly wind pattern for one day is shown in Figure 2.
Figure 2 Example Day-Ahead Hourly Schedule for a 30 MW Wind Farm
0.0
5.0
10.0
15.0
20.0
25.0
30.0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of the Day
MW
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ne aspect of assessing the cost of integrating wind is to assess the wind impact on short-term
planning over the coming day. Hourly production cost modeling is available to examine expected
hourly load patterns, unit commitment and dispatch aspects of the non-wind portfolio, prices and
availability of spot market purchases, and expected hourly patterns of the wind generation. These
models can be used to estimate one of the financial impacts of wind resource variability. Typically these
studies compare the cost of meeting load with a varying hourly (wind) supply to the cost of meeting load
if the energy from the wind had been delivered flat on all hours.
O
The hourly production cost model is first run with an assumed flat wind resource and then with the
expected hourly pattern of the wind, both patterns providing the same annual energy. The difference in
the annual production cost is then divided by the annual energy of the wind generation to get a “cost”
per MWh related to the wind shape. If the wind hourly pattern is better shaped to load than a flat wind
pattern, this “cost” can be negative (indicating a benefit to having that wind pattern over a flat wind
pattern). However, in most studies, the actual wind pattern is more costly than a flat wind pattern. The
cost determined from this study will be added to what it is estimated it will cost to avoid CPS2
violations.
The magnitude of the “cost” of the expected “shape” of the wind will depend on what other resources
are able to fill in around the wind shape. A larger utility with many flexible resources and larger
interconnections that can provide access to other resources will show much lower cost than will a
smaller utility with fewer flexible resources and little access to resources outside its boundaries.
Evaluating the “cost” of hour ahead changes from day-ahead schedules -- The analysis described
above reflects the ability of the system operator to “commit” different resources as needed to
accommodate an expected day-ahead wind pattern. However, once those units are committed, it may not
be easy to change the scheduling if it becomes clear that the wind in the next hour will not be at the level
assumed for that hour in the day-ahead scheduling process.
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There are other generating resources, however, that can be fairly easily re-committed within an hour or
less. For example, hydro generation with storage can often be changed quickly for a short period of time
to accommodate short term needs.7 “Fast start” gas-fired generators generally can be started within an
hour or less. As with the case of day-ahead cost of shaped wind, the magnitude of the “cost” of
accommodating an hour-ahead modification to a wind schedule will depend on what other resources are
able to fill in rapidly such as in an hour or less. A larger utility with many flexible resources and larger
interconnections that can provide access to other resources will show much lower cost than will a
smaller utility with fewer flexible resources and little access to resources outside its boundaries.
Evaluating the “cost” of within-the-hour variations of wind -- Wind variations on the very short term
can have an impact on frequency of the interconnected system. However, as discussed earlier, the
system has already been designed to deal with frequency variations. The FERC reliability requirement
dealing with load/resource imbalance issues are the control performance reliability requirements.
Therefore, in evaluating the cost of within-the-hour variations of wind we need to focus on the cost the
wind variation might have on an ability to meet these requirements. CPS2 is the most stringent of these
requirements.
The CPS2 reliability criteria do not separately deal with the cause of any CPS2 violation. These CPS2
violations can be caused by unanticipated load changes, unanticipated changes in output of non-wind
generators, or wind output that varies from forecast amounts. There is no FERC reliability criterion that
singles out wind performance. It is the combination of load and resource performance (including both
wind and non-wind resources) that affect CPS2 performance. That being the case, it is not possible to
know with a high degree of certainty what impact future wind generation might have on CPS2
performance, although a reasonable approximation is possible if there is a significant amount of
historical data available.
7 If a hydro unit output is changed for a short period of time, the operator will need to make future changes to its dispatch to replace that hydro generation so that reservoir levels meet mid-month or end-of-month elevation targets.
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Studies have attempted to estimate the impact that future wind will have on CPS2 performance and to
determine what amount of additional reserves in megawatts might be needed to mitigate any adverse
impact on CPS2 performance. It is widely believed that any such study will necessarily need to take into
account the “time synchronized” net wind-load data. That requires having a good estimate of the
simultaneous changes in wind and load. It is generally believed that balancing authority hourly (and 10-
minute) load variations are not correlated with hourly (and 10-minute) wind variations, although there
may be a measurable correlation specific to forecastable weather events. This is due in part to the reality
that the load is more temperature dependent and spread over a very large area while the wind generation
at any wind farm is more wind dependent and spread over a smaller area. Another complicating factor
for the analysis arises if there are many wind farms that result in a diversity of hourly and 10-minute
wind generation swings between the wind farms.
n most parts of the country, it is felt that existing levels of wind penetration are not causing operators
to incur high cost to integrate the wind. However, there are a few notable instances where there have
been claims that existing levels of wind generation have been problematic.8 Studies have attempted to
determine the integration costs of adding significantly more wind generation to the system. These
studies necessarily need to first determine the hourly and sub-hourly wind plant generation levels as well
as the volatility of that wind generation. High resolution wind speed or wind power production data is
necessary to accurately estimate the impact of wind generation on system operation on the appropriate
time scale.
I
8 In Montana, NorthWestern Energy claims it incurred significant costs to integrate the 135-MW Judith Gap wind project. This claim is based on the fact that NorthWestern Energy in Montana has no flexible resources and has not put in place an ability to change schedules across the interties to other control areas once hour-ahead schedules are set. News reports of a wind event in ERCOT in February of 2008 indicated that “Operators of the Texas power grid scrambled. . . to keep the lights on after a sudden drop in wind power threatened to cause rolling blackouts.” A later review of that event, however, concluded that the cause of the frequency excursion on that date could be attributed very little to an unforeseen rapid drop in wind generation and instead was caused by a number of other factors. One was that day-ahead wind forecasts were not being updated. It also appears that other (non-wind) unit outages precipitated the frequency excursion.
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ind speed data can be gathered from study area meteorological towers or by other data
collection and aggregation methods. Meteorological tower data can provide good estimates of
locational wind speed and direction variations at very high resolutions.9 Often, high-resolution
meteorological tower data is not available for potential wind sites because there are no on-site met
towers. Other reasons for the lack of data is that aggregated local data does not have the appropriate
resolution needed, does not cover an adequate time period for the estimation of the wind resource, or
does not represent the diversity of the wind resource over the study region.
W
In cases where there is no location-specific data of sufficient quality, studies will often use modeled
wind data.10 Such data is often used as an indicator of general areas where wind developers may want
to perform further investigation of the available wind resource. However modeled data is often
substituted for met tower data. This is because modeled data is generally the only homogeneous data
source with high enough resolution wind data available for the study region of a wind integration cost
udy.
ind
l
ropriate and resource-appropriate turbines must
e selected in order to maintain modeling credibility.
st
Wind speed data must be converted into wind generation data in order to determine the effect of w
power on a given system. Converting wind speed data into wind generation data can be done by
applying the instantaneous met tower wind speed data to wind turbine power curves and summing over a
given time period, or by determining the statistical characteristics of the wind data and estimating annua
average generation.11 A power curve from a region-app
b
9 Meteorological towers are the most common means for measuring the wind speed and direction at a site. These towers and their meteorological equipment collect and store data on wind speed and direction every three seconds at several different heights above the ground. This data is often averaged to hourly or sub-hourly time scales. 10National Renewable Energy Laboratory, for example, estimated historical wind data for a large number of wind areas of North America by running a Numerical Weather Prediction Model using physical conservation equations that “recreate the weather” for 2004 to 2006. 11 Such conversions, if applied to very short timeframes such as minutes, miss the reality of wind turbine inertia and sophisticated wind plant controls that can limit power output and ramp rates.
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ext, the within-the-hour changes to wind speed estimated above must be matched with within-the-
hour load changes to get a time-synchronized load-wind variation. Studies will then compare the
10-minute load variations without the wind to the 10-minute time synchronized load-wind variations to
see how much greater the variations are, along with the risk to CPS2 performance, when the wind
generation is added. It is recognized that the development of the 10-minute time synchronized load-wind
variations are often approximations due to the difficulty in obtaining time synchronized 10-minute data.
Studies that reflect wind penetrations in widely diverse geographic areas generally show less increased
risk to CPS2 performance because of the diversity of the wind volatility.
N
Once an estimate is developed of additional 10-minute net load variations that are incurred when adding
wind, it is next necessary to estimate the cost of mitigating that additional risk. What that cost will be
will depend on what other resources are able to fill in rapidly - on a 10-minute basis or less. A larger
utility with many flexible resources and larger interconnections that can provide access to other
resources will show much lower cost than will a smaller utility with fewer flexible resources and little
access to resources outside its boundaries.
Some studies simply assume that new reserve resources will need to be built to accommodate this
additional volatility, in effect neglecting the possibility that existing resources may be available in
enough time periods and of sufficient size to avoid violating the CPS2 90% requirement. For example,
assume that the planning reserve margin in a balancing authority is 15%, meaning there must be 15%
more firm supply (in megawatts) available to the balancing authority than the peak load. Further assume
that, without the wind, there is a need for 6% operating reserves on every hour. Then when wind is
added, assume there is a need for an increase in operating reserves from 6% to 7%. The cost to
accomplish the increased operating reserve need is part of the wind integration cost. It is possible that
the system already has sufficient resources built to provide the 1% increase in needed operating reserves
as long as the increased operating reserve can be accomplished through increasing contingency reserves
such as quick start units. If the additional need is for more regulating reserves, then it may be that the
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only thing required is to provide automatic generation control communication equipment to some
existing supply and to have that existing supply already spinning when needed.
In another example, it may be that there are no additional supplies in the balancing authority available to
provide additional needed operating reserves. In such a case, new quick-start generation or generation
that can be economically operated as spinning reserve will be needed. The capital cost of these new units
could be assigned to the cost of integrating the wind. Further, if a unit must be spinning, then the net
operating cost (the variable cost of operation less value of the energy) and any re-dispatch costs
necessary to accommodate the minimum generation requirements of the spinning unit could also be
assigned to the cost of integrating wind.
If it is determined that a cost effective method to manage the wind generation extremes would be
through wind curtailment, then the loss of some amount of wind generation needs to be reflected in the
cost of integrating the wind.
Review of studies done by others to estimate the cost of integrating wind -- A large number of studies
have been done that attempt to estimate the cost of integrating wind. Clearly some wind can be
integrated with the existing system at minimal cost. Some studies focus on how much wind can be
integrated with the existing system. Other studies attempt to determine the cost of integrating large
amounts of new wind, and try to determine what types and amounts of new resources might be needed
to do so. New wind integration studies continue to be performed and results published.
There are vastly different approaches being taken within the many wind integration studies. For
example, one such study might compare the total production cost of a system under two different
possible resource additions. One such addition would be a wind plant with an expected varying hourly
pattern. The alternative addition would be a zero variable cost resource that provides constant amount of
power every hour and the same annual energy as the wind plant. The difference in total variable power
costs between the two cases can be divided by the wind annual generation. Such an analysis might
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conclude that the difference in “value” to the utility between the flat resource and the wind resource is
$4/MWh. While this is an interesting analysis, it really does not get to the heart of the question of how to
deal with a wind resource with volatility that must be counter-acted to avoid frequency excursions or
CPS2 violations.
Another impact often evaluated in these studies concerns increased costs related to existing non-wind
generation. These cost increases are due to additional starts and hours online for peaking generators that
have quick-start capability and additional ramping of generators to meet hourly and intra-hour load
requirements due to variations in wind generation output. The ramping of generators often causes units
to operate at a less efficient heat rate and thus burn more fuel to generate the same amount of electricity.
The additional starts and hours online can hasten the need for major plant overhauls, thereby increasing
operation and maintenance costs for these units on an annual basis. How and if these additional costs are
incorporated in wind integration studies can lead to significantly different results, and is an important
factor to consider when evaluating the impacts of wind generation on the existing system.
Further, some studies will include an analysis of what resources might need to be added to "firm up" the
wind sufficiently for the utility to meet its planning reserve requirement. As discussed in Section 1, for
purposes of this report, additional supply needed to assure that the nameplate capacity of the wind can
be counted fully for resource adequacy (the Planning Reserve Margin) purposes is not considered a wind
“integration” cost. Any resource adequacy related cost associated with addition of wind is defined as a
planning cost much like transmission, but not an operating cost. However, because it is an important
aspect of understanding the cost of a resource portfolio that includes wind, Section V discusses this
issue.
Summary findings of other wind integration cost studies -- Based on the discussion above, it is clearly
not practical to perform an exhaustive review and commentary on all wind integration studies that have
been performed. A review of any wind integration studies would need to address not only the
differences in cost, but also the differences in the calculations and what exactly is being measured.
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The American Wind Energy Association has reviewed several such studies. Their findings show a wind
integration cost range that generally varies between zero and $5/MWh.12 This range of estimated wind
integration cost seems to be fairly widely accepted in the industry as indicative. The wind integration
cost for any particular control area or wind plant would best be estimated using the specific load,
resources, wind regime that is involved.
Impacts on Resource Adequacy When Wind Is Included in the Supply Portfolio
Resource adequacy-related costs associated with the addition of wind is defined as a planning cost much
like transmission, but not an operating cost. This section discusses the nature of that issue even though
any costs would not be considered “wind integration” costs as we have defined the term.
When significant amounts of wind are added to the system, additional non-wind supplies may need to be
added to assure resource adequacy. Whether this is true depends on a number of factors including
whether the wind supplies are sufficiently diverse such that they would be expected to be: a) all
providing very low output during the peak load hours, or whether they would be expected to be b)
providing considerable power during these hours. A wind “Effective Load Carrying Capability” (ELCC)
study can assess these probabilities.
The planning reserve margin needed to assure reliable service generally is established via studies that do
not directly reflect wind volatility. Assume that reliable service is defined as any portfolio that provides
a loss of load probability of not greater than one day in 10 years. Further assume that a loss of load
probability study indicates that a 15% Planning Reserve Margin is needed to meet the one-day-in-10-
year loss of load probability. In other words, if the system peak load is 10,000 MW, then resources with
capacity adding up to 11,500 MW will need to be available in order to provide the required reliability.
12 http://www.awea.org/utility/wind_integration.html
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an we count the wind at nameplate capacity when checking to see if we have adequate supplies?
The answer is “no” because we did not reflect the wind volatility in the loss of load probability
study. If we had reflected the wind volatility in the loss of load probability study, the Planning Reserve
would have been higher. A wind ELCC study will tell how much the wind capacity can be counted
toward the 11,500 MW needed in order to retain the same loss of load probability. Typically such
studies indicate that zero to 25% of the wind nameplate capacity can be counted toward the Planning
Reserve Margin requirement. The calculation needs to reflect the specific wind output regime of the
identified wind farms.
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If a utility already has sufficient resource adequacy capacity to meet its Planning Reserve requirement
but needs more renewable generation to meet renewable portfolio standard (RPS) goals, then there is no
need to add more capacity when wind is added. Since RPS goals are energy goals that are supposed to
be met whether there is a need for new capacity, it is often the case that no new resource adequacy
capacity is needed. However, in adding the wind in this situation, the operating capacity factor of the
existing resource adequacy capacity may be reduced. In these cases the “clean” wind energy is simply
displacing fuel that would have been used to provide energy from the existing thermal capacity.
In summary, whether new “firming” resources will be needed depends on whether new capacity is
needed to meet Planning Reserve Margin requirements.
There is also the question of whether FERC will need to change its reliability criteria if significant
additional amounts of wind are added to the system. For example, will the Control Performance
Standard (CPS2) requirement continue to be adequate if significant amounts of additional wind are
added to the system? Clearly there will be discussions around this issue in the future. However, as long
as (a) Planning Reserve Margins are appropriately set and (b) wind is being appropriately counted
toward meeting these margins (something less than 25% of wind capacity being counted), then it would
seem that FERC will not need to change its reliability criteria as demonstrated in the following example:
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Assume that a very large control area is counting no wind towards resource adequacy and that it
has a 15% Planning Reserve Margin. Even with a massive amount of wind -- 50% of energy --
introduced into the system, there needs to be enough firm capacity to cover 115% of the peak
load. The need for Resource Adequacy capacity drives the need for new non-wind resources, and
the only impact of the wind is that we are adding a lot of wind that does not contribute toward
the needed resource adequacy capacity. The calculation is as follows:
Assume: • The plan is to have wind provide 50% of energy needs (50% RPS). • Wind resource adequacy count is zero, and • Planning Reserve Margin requirement is 15%. • Annual Peak load is 10,000 MW. • Energy Load is 48,180 GWh (55% Load Factor).
Then: • Resource adequacy generation needed is 11,500 MW (15% PRM required). • Wind Generation is 24,000 GWh (9,132 MW of wind at 30% capacity factor). • Generation Mix is
o 1,000 MW nuclear. o 1,000 MW coal. o 4,000 MW combined cycle. o 5,500 MW gas turbine.
Total: The 11,500 MW needed for resource adequacy purposes. As can be seen, there is plenty of capacity available at all times (barring large overlapping unit forced
outages). It may be that on low load hours there is a need to back down coal and/or nuclear or feather
out wind. That makes variable operating cost at those times near zero.13
13 Is that a problem? No, it just has the economic impact of causing marginal costs to approach zero. This is not new in the industry. It is very much like the situation today in the Northwest when very large spring hydro runoff caused by snowmelt causes extremely high hydro generation levels when loads are down. In some of these instances there is so much hydro generation that all thermal units are shut down or are reduced to minimum, tie lines that can move power outside the region are fully loaded, yet there is still so much river flow that all the water can not be run through turbine generators because there is not enough demand for the power. In these situations, water is spilled past unused turbines and spot market prices approach zero.
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While there is sufficient capacity to cover all wind conditions, from an operational perspective we need
to be assured that enough of the capacity is being provided by flexible (quick start) resources sufficient
to cover massive changes in the wind generation. Much of that wind change should be easily forecast, so
we can arrange to have the right amount of peaking units running when the wind is not expected to be
there. With all of this capacity available, even if large amounts are running because the wind generation
is low, there still remains sufficient additional capacity to provide for operating reserves. In other words,
if wind is expected to be zero, then the gas units are scheduled to meet load and not needed to be
available to cover a drop in wind since we are already assuming it will be zero. If wind is maxing out,
then few of the gas units are needed and all can be available for reserves. So in this case, since we count
wind as zero resource adequacy, then the need for resource adequacy resources should cover what we
need in order to integrate the huge amount of wind.
What if we count wind as 100% toward resource adequacy rather than zero? Then we have an operating
issue. Or we must raise our Planning Reserve Margin to a number much larger than 15%. But no utility
or balancing authority counts wind 100% toward resource adequacy. Most utilities count wind
somewhere between zero and 25% of nameplate capacity. So the zero example above is quite realistic.
There is another issue that deserves consideration. While there may be plenty of quick-start gas-fired
generation on hand to offset rapid drops in wind generation, one needs to be assured that the fuel system
can accommodate the quick start units.
Methods To Mitigate The Cost of Integrating Large Amounts of Wind
A larger utility with many flexible resources and larger interconnections that can provide access to other
resources will show a much lower wind integration cost than will a smaller utility that does not have
these advantages. In order to accommodate larger penetrations of wind, a number of suggestions are
being evaluated including:
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Improved wind forecasting is the best method of dealing with the volatility of the wind output. The earlier the operators can get an indication of change, the more time is available to find the most economic source of alternate power.
Creating regional transmission organizations (RTO) with centralized markets that expand across a broader geographic area and encompass more generation facilities than a single small control area.14
Where RTOs are not being created, smaller control areas are rolled into larger control areas.
Where control areas are not being combined, efforts are being made to develop:
o Business practices to allow within-hour scheduling and within-hour purchase of existing transmission products.
o Automated information exchange for information regarding the state of participating
systems, including an individual generator’s ability and prices to increase or decrease. o Automated mechanisms to access system flexibility swiftly and efficiently through
communication links that tie to the Open Access Same Time Information System (OASIS) for transmission access purposes.
o Dynamically metering wind located in one control area into the control area where
the wind output is being sold -- presumably a control area with better access to flexible resources.
o Demand resources with the necessary controllability may provide the equivalent of
regulating reserves and operating reserves. FERC has ordered that demand resources be given the same opportunities as conventional generation to participate in the supply of ancillary services in organized markets.
Any of these suggestions can help accommodate the integration of increased amounts of wind at a lower
cost by taking advantage of existing capabilities in the system.
14 The diversity provided by the larger area is beneficial with regard to integration costs. The standard deviation of the forecast error of each sub-area that comprises an area is not additive. Hence, while the standard deviation of the forecast error grows as more and more sub-areas are integrated into a single control area, the error as measured as a percentage of load-wind level shrinks as more and more sub-areas are added. Hence, the error is easier to manage.
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Insights Gained From Large Control Areas Regarding Wind Integration
Alberta: The Alberta Electric System Operator (AESO) began to get nervous about how much wind
it could reliably integrate into the system. As such, in April 2006 the AESO instituted a 900
MW cap on wind in their system until they could better understand the impact. The AESO
recognized that it was important, both to system reliability and to the successful
development of renewable resources in Alberta, that the impact on power system
operations be understood as Alberta reached new levels of wind penetration. Alberta then
studied its system and concluded that an appropriate framework for addressing additional
amounts of wind could be put in place that, if followed, could allow any wind to be
developed that the market desired. Their report entitled “Market & Operational Framework
for Wind Integration in Alberta” was dated September 26, 2007. The Market &
Operational Framework replaced the 900 MW threshold that was implemented in April
2006 allowing investment decisions regarding the supply portfolio in Alberta to be driven
by market forces.
California: At the request of the California governor’s office, the California Independent System
Operator (CAISO) has worked with stakeholders to develop a Participating Intermittent
Resource Program. This program creates conditions for intermittent producers to bid into
the California forward market without incurring 10-minute imbalance charges when the
delivered energy differs from the scheduled amount. Instead, participants are assessed
deviation charges based upon monthly net deviations between the metered and scheduled
energy. An unbiased forecast of hourly energy results in a net energy deviation over an
entire month that approaches zero. If the wind generation units were being directly exposed
to the uninstructed deviation charges, they would experience significant difficulties while
competing in the energy market. The Participating Intermittent Resource Program helps the
participating wind generation units to avoid minute-by-minute uninstructed deviation
charges and become competitive energy market players. In essence, the CAISO has
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concluded that it will do what is necessary to assure that it avoids CPS2 violations even
with significant penetrations of wind. The CAISO does not intend to perform a study to
assign the responsibility for its needed operating reserves to load or generation. Just as it
had done since its inception, the cost of the operating reserves necessary to accommodate
load and generation swings will be assigned to the transmission access charge and will
become a cost assigned to load.15
Summary of Wind Integration Issues
When integrating wind, it is not necessary for the power system to exactly match wind output with
scheduled output. Variations in scheduled and actual output will affect system frequency. But there is,
and always has been, an ability of the system to live with a certain amount of frequency variation.
Governor controls on generating units throughout the interconnection generally provide an ability to
keep frequency variations within tolerable variations. As wind penetration increases, however, governor
controls may be stressed more and may hit limits not encountered under lower wind penetration levels.
The mandatory reliability requirement that most directly relates to wind volatility is the control
performance standard CPS2. Control Area operators that accommodate more wind will want to avoid
CPS2 violations when integrating the wind.
It is very difficult to estimate in advance exactly what will be needed to avoid CPS2 violations when
integrating planned new wind generation. This difficulty arises because of the lack of good data on what
the wind variation will actually be and, even more difficult, the lack of good data on time synchronized
load-wind variation. However a plausible worst case can be developed that would set the ceiling for
wind integration costs with the currently available data sets.
15 The CAISO approach assumes that the wind in its control area is being used to serve load in its control area. If the CAISO is asked to perform control area services for wind that is to be wheeled out of its control area, the CAISO will likely want to charge the wind plant for those services.
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arger utilities with many flexible resources and larger interconnections that can provide access to
other resources will show much lower cost than will a smaller utility with fewer flexible resources
and little access to resources outside its boundaries. The benefits of having access to a larger system to
help integrate wind can be accomplished through a number of methods including forming RTOs across a
larger region, combining control areas, or simply setting in place business practices that can be used to
effectuate the ability to use the entire capability of the interconnect.
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Alberta and California have addressed wind integration issues and have concluded that large amounts of
wind can be integrated as long as care is taken to assure that sufficient flexible resources are available to
meet CPS2 requirements. California has determined that it is not necessary to identify which of their
flexible resources are needed for load swings and which are needed for wind swings since they intend to
charge load for the cost of all needed flexible resources.
Any wind integration study is necessarily customized to the area load, wind projects, and non-wind
resources that are available. A study that identifies a particular wind integration cost per kilowatt hour
for one control area or level of wind penetration will likely be different for another control area or level
of wind penetration. A range of wind integration costs between 0 and $5/MWh are reflective of such
differences in control area loads, wind projects, and non-wind resources that are available as well as
different overall approaches to the analysis.