Integrating Wind Generation into the Grid -- A Primer

Transcription

1 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

2 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 Methods to Mitigate the Cost of Integrating Large Amounts of Wind Insights Gained From Large Control Areas Regarding Wind Integration Summary of Wind Integration Issues... 22

3 T 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. 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: 1

4 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? 2

5 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. 3

6 S 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. 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 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. 4

7 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 5

8 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 ACE 5 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 = (NI A - NI S ) - 10b (F A - F S ) T ob + I ME Where: NI A represents actual net interchange (MWs). NI S represents scheduled net interchange (MWs). b represents the control area's frequency bias setting (MW/0.1 Hz). F A represents actual system frequency (Hz). F S represents scheduled system frequency (60.0 Hz in North America). T ob represents scheduled interchange energy used to bilaterally correct inadver10t accumulations (MWs). I ME represents a manually entered amount to compensate for known equipment error (MWs). 6

9 A ssume for purposes of this discussion that L10 for a particular balancing authority is 24 megawatts (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. 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. 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. 7

10 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 MW Hour of the Day 8

11 O 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. 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. 9

12 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. 10

13 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. I 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. 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. 11

14 W 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. 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 study. Wind speed data must be converted into wind generation data in order to determine the effect of wind 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 annual average generation. 11 A power curve from a region-appropriate and resource-appropriate turbines must be selected in order to maintain modeling credibility. 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. 10 National 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 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. 12

15 N ext, the within-the-hour changes to wind speed estimated above must be matched with within-thehour 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. 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 13

16 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 14

17 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. 15

18 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

19 C 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. 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: 17

20 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 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. 18

21 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: 19

22 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 loadwind level shrinks as more and more sub-areas are added. Hence, the error is easier to manage. 20

23 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, 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 21

24 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. 22

25 L 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. 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. 23