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Ancillary Service Adequacy Assessment with KERMIT. March, 2013. Outline. Motivation (limitation of hourly models, need for intra-hour analysis) ERCOT Market functions for short-term commitment and balancing decisions (DRUC, HRUC, SCED)
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Ancillary Service Adequacy Assessment with KERMIT March, 2013
Outline • Motivation (limitation of hourly models, need for intra-hour analysis) • ERCOT Market functions for short-term commitment and balancing decisions (DRUC, HRUC, SCED) • Overview of KEMA Renewable Market Integration Tool (KERMIT) • Review of preliminary study results (S3 and S8) • Improvements in progress
Overview of initial DOE Transmission Planning Process Future generation mix scenario Production Cost Simulation (PROMOD) Is solution feasible? No Feasibility Metric: Plant Economics & Planning Margin, 13.75% Transm. upgrades Yes Transm. violations? Yes No Results
DOE Scenario Examples S8, 2016, 39 GW of new wind S3, 2022, 7GW of new wind, 2.5 GW solar Economic assessments performed as part of the DOE project suggest increasing proportions of wind energy are probable on the ERCOT system. We need to assess the adequacy of operational reserves for increasing proportions of wind and solar generation.
Motivation for Improvement of the Study Process • Production cost simulations do not consider intra-hour production variability of the renewables • High renewables scenarios may require higher operating reserves to balance generation variability and achieve acceptable frequency performance. • Consideration of higher operating reserves may impact the economics of a future generation mix. • Need for new sub-process in a Long Term Transmission Planning Study that will capture: • Renewable power production uncertainty, • Renewables power production variability, • Relevant ERCOT market and operation processes that are used to balance production and consumption
Improvement of the Study Process Feasibility Metric: Plant Economics & Planning Margin, 13.75% Feasibility Metric: System Frequency, Control Performance Std. (CPS1≥ 100%) New sub-process in a Long Term Study
Relevant ERCOT Electricity Market Processes DRUC / HRUC ERCOT market processes determine short term commitment decisions for changing market conditions (e.g. renewables production uncertainty): • Day Ahead Reliability Unit Commitment (DRUC), is 10-34 hours look-ahead; • Hour Ahead Reliability Unit Commitment (HRUC), is down to 1 hour look-ahead, SCED addresses net load variability in near-real time: Security constrained economic dispatch (SCED), at least 5 minutes in operating hour to meet intra-hourly variations in load/wind, using telemetered output and resource limits.
System balancing (within 5 mins), Ancillary Services • To balance variability of load and variable generation and compensate for generation outages, Ancillary Services are procuredthrough day-ahead market and deployed in real time • Three types of ERCOT Ancillary Services: • Regulation up, Regulation down (AGC) • Responsive reserve (gen. governor response, underfrequency load resources) • Non-spin Generation Output Net load
Relevant ERCOT market and Operation Processes Inertia response First few seconds Governor response 10-30 seconds Regulation (AGC) 20 seconds to 5 minutes Economic Dispatch every 5 minutes Unit Commitment Every hour
New sub-process in Transmission Planning • Assesses the ability of the ERCOT market and system to manage inherent variability and uncertainty in renewables at multiple timescales • Using a tools that integrate ERCOT’s multiple scheduling and operation processes, with multiple time resolutions, relevant to ERCOT: • RUC, hours - (PROMOD) • SCED, 5-minutes - (KERMIT) • Governor Response and AGC, seconds - (KERMIT) New sub-process in Long Term Study
Overview of KERMIT Wind power forecast versus actual Load rejection Volatility in renewable resources Generator trip Inputs: Load Plant Schedules Generation Portfolio Grid Parameters Market/Balancing KERMIT 24h Simulation Outputs: Power Plant MW Outputs Area Interchange Frequency Deviation • Generation • Conventional • Renewable Frequency Response Scenarios: Increasing Wind Adding Reserves Storage Parameters Test AGC Parameters Trip Events Inter- connection Real Time Market • KEMA’s Renewable Market Integration Tool, Simulink/Matlab/Excel • Simulation of second-by-second system operation, for 24 hour horizon • Given a user-defined set of inputs, KERMIT will provide an assessment of a system’s ability to achieve adequate balancing and maintain system frequency.
KERMIT Inputs • Load data (secondly) • Generation commitment (hourly) • Unit Operational / Economic data (Unit capacity, type, reserve obligations, cost curves, ramp rates, inertia constants etc.) • Wind/Solar data (secondly) • Settings for generators’ frequency response, Automatic Generation Control, Underfrequency load relays. • Simplified representation of transmission constraints
Feature specific to ERCOT’s AS study To represent potential transportability of Ancillary Services, ERCOT developed a simplified network representation (“Pipe and bubble” model);
Modules in KERMIT KERMIT Modules Inertia response First few seconds Governor response 10-30 seconds Regulation (AGC) 20 seconds to 5 minutes Economic Dispatch every 5 minutes Unit Commitment (PROMOD) Every hour
KERMIT Outputs • Generator power outputs • System frequency (with 1 second resolution) • Deployment of reserves
KERMIT model calibration to 2011 ERCOT operation • ERCOT system model developed in KERMIT was calibrated to the historical system operation data (2011) during normal situations and extreme events; • KEMA identified 3 days in 2011 (02/15, 5/19, 11/29) to represent normal and extreme system operation. • Actual loads, SCED instructions, wind power production, and forced generation outages were used as input for 3 simulated days • KEMA and ERCOT simulated 1 operation day to calibrate the KERMIT model parameters. • KEMA and ERCOT simulated 2 other days to show suitability of calibrated model.
Frequency for Nov 29, 2011 Event KERMIT was able to sufficiently replicate historical large events both in terms of frequency excursion and recovery time
Metrics to use for AS adequacy analysis For representative days (22) in a year real time operation is simulated with KERMIT The following metrics are used to assess AS adequacy of future generation scenarios: • Sufficiency of available resources to balance renewables and load variability 5-minute to 5-minute (SCED timeframe) • Sufficiency of reserves to balance renewables and load variability within each 5 minute interval. • System frequency second to second and • Compliance with CPS1 score, (CPS1 ≥ 100%), If AS adequacy is not established, higher reserve requirements are added to PROMOD and study is re-ran. This changes might affect economics of the generation build.
Preliminary results, S3 Scenario S3 has nearly 7 GW of additional wind generation by 2022. The preliminary results from the KERMIT study show: • Hourly commitment in S3 does not have sufficient dispatchable capacity to follow 5-minute to 5-minute net load ramp-ups in spring and autumn months (low load/high wind situations) in SCED timeframe; • Non-Spin reserves, 1700 MW (as per PROMOD model), need to be dispatched more often then currently to resolve this issue • Without Non-Spin reserves, weighted average CPS1 over a year is 96% – no compliance with NERC requirement; • With Non-Spin reserves, weighted average CPS1 over a year is 165%. The compliance is achieved, similar to current CPS1 score.
Dispatch of non-spin reserves, S3 • 683 hours of non-spin reserve dispatch a year, compared to just a few hours currently; • Maximum dispatch level is 1350 MW. Full ramping capability 1700 MW/15 min is used in some dispatch intervals ;
Preliminary results, S8 Scenario S8 has nearly 40 GW of additional wind generation by 2016. The preliminary results from the KERMIT study show: • Hourly commitment in S8 does not have sufficient dispatchable capacity to follow 5-minute to 5-minute net load ramp-ups in some hours in the most of the simulated days. • Non-Spin reserves, need to be increased to 3500 MW, to resolve this issue, (or other kind of reserves introduced in SCED timeframe). • In the evenings and nights, conventional generators are dispatched close to Low Sustainable Limits (LSL) and are not able to follow 5-minute to 5-minute net load ramp-downs in SCED timeframe. • Without any additional measures, yearly CPS1 score is extremely low. • ERCOT added an option of wind energy curtailment in SCED during evenings and nights to resolve this issue. • With this measures CPS1 score of 156% can be achieved in S8
Non-spin dispatch S8 • 1220 hours of non-spin dispatch a year, compared to just a few hours currently; • Maximum dispatch level is 1450 MW. But full ramping capability of 3500 MW/15min is used in some dispatch intervals; • If faster ramping technology is available, with ramping capability of 1200 MW/5min. Less reserve capacity would be required.
Wind energy curtailment in 5 min dispatch • 840 hours of wind energy curtailments a yearfor dispatch only • Maximum curtailment as high as 3300 MW in some dispatch intervals • Total of about 400 GWh of wind energy curtailment a year; • equivalent of 8 hours production at full wind generation capacity (50 GW) a year
Improvements in Progress • Determine additional Regulation Reserve requirement for S8 • Test generation trips in S3, S8, S4 => additional RRS? • Test scenario S4 (environmental scenario with energy efficiency and DR) in KERMIT • Modify PROMOD with new non-spin and spinning reserve requirement and re-run PROMOD studies. • Analyze the changes in PROMOD, another iteration in KERMIT might be necessary for scenarios S8 and S4.
Appendix: Scenario 4 (Environmental with Energy Efficiency and Demand Response)
Appendix, new wind projects in S8 (2016) Zone MW NORTH13 260 NORTH CE766 WEST5 490 SOUTH CE200 SOUTH17 809 Austin601 Dallas776 Total 38 900
Appendix, new wind projects in S3 (2022) Zone MW NORTH4792 NORTH CE205 WEST1 971 Total 6 968 Wind (7 GW) Solar (2.5 GW) Gas (17.9 GW)