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Target Reserve Margin (TRM) and Effective Load Carrying Capability (ELCC) of Wind Plants Evaluation - Input and Methodology. ERCOT Planning. Target Reserve Margin Discussion - Meeting Agenda. Reliability Indices Input Data Generation Assumptions Maintenance and Outage Data
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Target Reserve Margin (TRM) and Effective Load Carrying Capability (ELCC) of Wind Plants Evaluation - Input and Methodology ERCOT Planning
Target Reserve Margin Discussion - Meeting Agenda • Reliability Indices • Input Data • Generation Assumptions • Maintenance and Outage Data • Load and Wind Profiles • Study Methodology • Comparison to 2007 study by Global Energy Decisions
Study Overview • The scope of this study is to evaluate the relationship between generation reserve levels, system volatility and inherent system reliability. • The following components of system volatility are being considered: • Generating facilities outages • Load uncertainty related to weather and economic growth • The intermittent nature of wind power
Reliability Indices • Loss of Load Expectation (LOLE) [1] • LOLE is the expected number of days per year for which available generating capacity is insufficient to serve the daily peak demand (load). • The LOLE is usually measured in days/year or hours/year. The convention is that when given in days/year, it represents a comparison between daily peak values and available generation. When given in hours/year, it represents a comparison of hourly load to available generation. • Other indices: • Loss-of-load hours (LOLH). • Loss-of-load events (LOL-Events). • Expected unserved energy (EUE).
Study Input Data – Generation Assumptions • All existing, as well as future resources with a signed interconnection agreement, that are expected to be in service in year 2012 are being considered, including units under reliability must-run (RMR) review. • The import capacity of the DC ties is not taken into account. • Monthly capacity multipliers are applied in order to model the seasonal capacity ratings of thermal units and the availability of hydro. • Scheduled outages for each iteration are selected from an index developed by ERCOT. • Forced outages are being modeled in accordance with available NERC GADS data.
Study Input data – Unit Outage Data • The following NERC GADS data are being used: • Net Maximum Capacity (NMC). • Service Hours (SH) • Forced Outage Hours (FOH). • Equivalent Forced Derated Hours (EFDH). • Number of forced outage occurrences. • Scheduled Outage Hours (SOH). • Number of scheduled outage occurrences. • When available, the data will be unit specific. • NERC definition for EFOR: (FOH + EFDH) / (FOH + SH + EFDHRS) • For more information right-click here to access the generating unit statistical brochure published by NERC.
Study Input Data – Load and Wind Profiles • Hourly load profiles for year 2012 prepared by ERCOT. • For more information on the load forecasting methodology applied by ERCOT right-click here to access the 2009 long-term hourly peak demand and energy forecast report. • Wind plant specific hourly wind energy availability data provided by AWS Truewind. • For more information right-click here to access the wind generation assessment report prepared for ERCOT by AWS Truewind.
Study Methodology • Transmission modeling • The transmission network is not being modeled. The ERCOT system is being represented as a single node. • Generation modeling • For each generator, for each iteration, a sequence of periods during which the unit is available and unavailable to provide energy (two-state model) is generated using a MATLAB-based model (sequential Monte Carlo approach). • Wind generation modeling • Since the transmission network is not being considered the wind-farm-specific hourly profiles are aggregated. To capture the randomness of wind generation, wind profiles are generated by randomizing the available daily profiles using a MATLAB-based model.
Study Methodology • Wind generation modeling (cont.) • Forced outages of wind turbines due to mechanical damage are not being modeled. • Hourly chronological load patterns have been developed in order to capture weather related and economic growth related uncertainty. • Load and generation from private use networks will be incorporated. • Generation levels will be adjusted in order to evaluate the impact of reserve margin levels on reliability indices.
ELCC calculation • Proposed method for the calculation of the ELCC: • ERCOT will be evaluating the ELCC of wind units by comparing them to combined cycle and gas turbine units. • The addition of X MWs of wind units should be achieving the same reliability level as the addition of Y MWs of the benchmark unit. The ELCC in per cent would then be (X/Y)*100. • ERCOT has identified that the ELCC may be sensitive to different reserve margin levels. This issue will be discussed further when draft results are available.
Study Results • The following estimates will be provided for year 2012: • The target reserve margin for the ERCOT region. • The ELCC of wind generation. • The annual loss-of-load expectation (LOLE). • The annual loss-of-load hours (LOLH). • The annual loss-of-load events (LOL-Events). • The annual expected unserved energy (EUE). • The percentage of EUE = [EUE/(Annual energy served + EUE)]*100
Comparison to the 2007 study by Global Energy Decisions • The study to be performed by ERCOT will compare to the 2007 Global Energy Decisions study in the following way: • ERCOT will be modeling all hours of the year instead of a representative week for each month. • ERCOT will be performing a much higher number of iterations in order to ensure the statistical significance of the results. • Wind will be modeled in a more dynamic fashion. Instead of randomizing days within an entire month, the wind profile for each day will be selected from representative profiles centered on that day.
Discussion Questions? Please contact Kevin Hanson at khanson @ercot.com
References [1] North American Electric Reliability Council, “Resource and Transmission Adequacy Recommendations,” Prepared by the Resource and Transmission Adequacy Task Force of the NERC Planning Committee NERC Board of Trustees, June 15, 2004.