June 29, 2010 Michael Milligan, Ph.D. National Renewable Energy Laboratory Golden, Colorado USA

1. Alaska Wind Integration Meeting June 29, 2010 Michael Milligan, Ph.D. National Renewable Energy LaboratoryGolden, Colorado USA NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy operated by the Alliance for Sustainable Energy, LLC

2. Outline • NREL’s Transmission and Grid Integration Group (TGIG) • High-level lessons learned about wind integration • Frequently-asked questions about wind integration (taken from Power and Energy magazine, 2009) • Best-practices for integration studies • Alaska: what applies vs. what does not National Renewable Energy Laboratory Innovation for Our Energy Future

3. NREL’s TGIG • Wind integration R&D since 1992 • Close collaboration with • UWIG • IEEE Wind Power Coordinating Committee • NERC Variable Generation Task Force • WECC Variable Generation Subcommittee • Western Governors Association (CDEAC and WREZ) National Renewable Energy Laboratory Innovation for Our Energy Future

4. NREL’s TGIG Integration • Extensive methods development • 100’s of technical papers on wind integration (www.nrel.gov/publications) • Focus on economically efficient approaches to integrating wind, maintaining (or improving) system reliability • Data driven • Scientific method National Renewable Energy Laboratory Innovation for Our Energy Future

5. NREL’s TGIG is involved… • Technical review committees • Xcel: MN, CO, multiple studies • MN statewide study • Pacific Northwest • BPA • PacifiCorp • PGE • California • RPS Integration Study • Intermittency Analysis Project • International Energy Agency Task 25 • Hawaii • ISO-NE, MISO, NYISO • Hawaii • NERC • FERC • WECC National Renewable Energy Laboratory Innovation for Our Energy Future

6. TGIG: Major integration studies • Eastern Wind Integration and Transmission Study • Western Wind and Solar Integration Study • Extensive work in Hawaii National Renewable Energy Laboratory Innovation for Our Energy Future

7. High-level lessons learned about wind integration into the power system • Results are system dependent • Size of system • Wind penetration and geographic mix • Time-step for economic dispatch, markets, scheduling • Composition of generation non-wind generation fleet • Flexibility: ramping, minimum run-levels • Institutional barriers can be significant drivers National Renewable Energy Laboratory Innovation for Our Energy Future

8. Flexibility requirements • Driven by physical power system needs (balance supply and demand) • Physical flexibility is required • Institutional barriers can prevent access to physical flexibility National Renewable Energy Laboratory Innovation for Our Energy Future

9. Wind increases the need for flexibility (ramp, turn-down/turn-off) Steeper ramps Lower turn-down National Renewable Energy Laboratory Innovation for Our Energy Future

10. In a closed system… • Adding wind does not require additional capacity • Adding wind does change the way that the balance of system capacity is utilized National Renewable Energy Laboratory Innovation for Our Energy Future

11. Better use of existing flexibility • Tap into maneuverable generation that may be “behind the wall”1 • Provide a mechanism (market, contract, other) that benefits system operator and generator • Fast energy markets/frequent dispatch/schedule changes help provide needed flexibility2 and can often supply load following flexibility at no cost3 1Kirby & Milligan, 2005 Methodology for Examining Control Area Ramping Capabilities with Implications for Wind http://www.nrel.gov/docs/fy05osti/38153.pdf 2Kirby & Milligan, 2008 Facilitating Wind Development: The Importance of Electric Industry Structure. http://www.nrel.gov/docs/fy08osti/43251.pdf 3Milligan & Kirby 2007, Impact of Balancing Areas Size, Obligation Sharing, and Ramping Capability on Wind Integration . http://www.nrel.gov/docs/fy07osti/41809.pdf National Renewable Energy Laboratory Innovation for Our Energy Future

12. Wind is pushing the power system • …to improve efficiency generally • Methods will increase economic efficiency without wind • One economic option: curtail wind and/or limit wind up-ramps National Renewable Energy Laboratory Innovation for Our Energy Future

13. Large, infrequent 5-Minute Ramps can be significantly reduced with large-area energy management Milligan & Kirby 2008, An Analysis of Sub-Hourly Ramping Impacts of Wind Energy and Balancing Area Size: http://www.nrel.gov/docs/fy08osti/43434.pdf National Renewable Energy Laboratory Innovation for Our Energy Future

14. What helps wind integration? • Larger effective electrical footprint • Physical consolidation • Various cooperative methods • Faster dispatch/scheduling • Storage • Electrical • Fuel • Inertia National Renewable Energy Laboratory Innovation for Our Energy Future

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17. Integration Issues for Alaska • What applies? • Generation diversity • Geographic diversity • Big and Fast • Institutional scheduling rules • What doesn’t? • Size (not so big, but can still be fast) • Smoothing from geographic dispersion of wind, loads, generation will be limited but will still be a factor National Renewable Energy Laboratory Innovation for Our Energy Future

18. Integration Issues for Alaska • What may be potentially required? • Faster ramping capability • Source: physical (aeroderivative turbines) • Source: institutional: broader balancing areas, fast scheduling, ACE Diversity, coordinated operations • Lower turn-down: can be achieved by BA cooperation and technology • Limitation: large interconnection National Renewable Energy Laboratory Innovation for Our Energy Future

19. Analysis is needed • Wind and load data (time-sync) • Establish range of need for flexibility • Alternative time frames • Production simulation • Realistic data from conventional system • Wind and load (time sync) • Potential platform to evaluate mitigation alternatives National Renewable Energy Laboratory Innovation for Our Energy Future

20. Study Best-Practices • Start by quantifying physical impacts • Detailed weather simulation or actual wind power data • Ensure wind and load data from same time period • Divide the physical and cost impacts by time scale and perform detailed system simulation and statistical analysis • Regulation • Load following and imbalance • Scheduling and unit commitment • Capacity value • Utilize wind forecasting best practice and combine wind forecast errors with load forecast errors • Examine actual costs independent of tariff design structure

21. Stakeholder Review Best Practices • Technical review committee (TRC) • Bring in at beginning of study • Discuss assumptions, processes, methods, data • Periodic TRC meetings with advance material for review

22. What is required for analysis? • Chronological wind and load data • Synchronized • If fast (minute) data are not available, NREL has database that can be used • Quantify requirements on alternative time scales • Data analysis and/or simulation National Renewable Energy Laboratory Innovation for Our Energy Future

23. Challenges identified by EPS • Islanded power system • Regulation • Transmission capacity/regulation • Wind forecasting and scheduling • Dispatch/control responsibility • Control agreements/responsibility • LVRT • Frequency ride-through requirements National Renewable Energy Laboratory Innovation for Our Energy Future

24. Challenges identified by EPS • Inefficiency of hydro/thermal • Transient stability • Transmission access • Storage identified as a solution • Other sources of flexibility may be more economic or complement storage • What time-frame for storage? • Regulation (fly-wheel, battery) • Load-following (pondage, battery, fuel) • Longer-term National Renewable Energy Laboratory Innovation for Our Energy Future

25. Addressing the challenges • Identifying the issues is a good start • Data and analysis is the only way to evaluate the significance of the issues identified by the EPS report • Detailed and synchronized data for wind and load are required • Quantify • How much • How fast • How often • This is a common theme going forward • Combination of data analysis and simulation may be required National Renewable Energy Laboratory Innovation for Our Energy Future

26. Islanded power system has limited electrical dispersion • No interconnection • Limited benefit of geographic dispersion (wind and load) • Limited generation portfolio/flexibility • Potential solutions • Dynamic schedules • ACE diversity interchange • Coordinated unit commitment, economic dispatch National Renewable Energy Laboratory Innovation for Our Energy Future

27. Regulation • Each delta in wind does not need to be matched 1-1 by conventional generation • Aggregate load = aggregate generation • AGC reacts to generation changes AND load changes • Wind has relatively small impact on AGC • 1-minute load and wind data, time-sync’d, are required to analyze the significance of this National Renewable Energy Laboratory Innovation for Our Energy Future

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29. Longer changes in wind output • …do have a potential impact on other generation • Less efficient (btu/kWh) generation but normally will be less fuel and emissions produced (wind saves fuel) • Conventional generation fleet will respond to wind and load changes, not just wind alone • Substantial body of evidence shows this impact is nonlinear and variable, and can be partially predicted in operational time frame • Individual response is limitedcooperation among BAs is helpful National Renewable Energy Laboratory Innovation for Our Energy Future

30. Longer changes in wind output • How to address this issue: • Synchronized wind and load data • Statistical analysis • How big is the impact (hourly) • How *often* are the impacts big/medium/small • What mitigation measures are needed? • Additional movement of committed generation • Out-of-merit dispatch • Occasional wind curtailment (partial) • Economically efficient measures should be identified and ranked/implemented National Renewable Energy Laboratory Innovation for Our Energy Future

31. Ramp limitations • Ramp rate of wind ≠ required ramp rate of conventional generation • Required ramp from conventional units is netted from load and wind together • Short time scales seconds to a few minutes will have relatively small impacts • Larger impacts 10s of minutes and longer • Detailed time-synchronized data will inform this issue • Data analysis • Possible system simulation National Renewable Energy Laboratory Innovation for Our Energy Future

32. Scheduling protocols • Spreading response is economic and will increase reliability • Thermal and hydro can both respond, based on what is economic and based on achievable ramping by each unit: EPS does not quantify what is needed nor what can be acquired • Simulation of unit commitment/dispatch based on wind, load, generation characteristics • Economic solution allows multiple units to respond, based on economics and physical constraints • Optimal: fast dispatch/schedules (5-minutes) National Renewable Energy Laboratory Innovation for Our Energy Future

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34. Transmission capacity/regulation • When wind generates power, other units must back down (or load must increase) • This will create room somewhere on the transmission system (maybe/maybe not in the “right” location) • Transmission that is required for regulation or imbalance is incremental, based on total system balance, not total wind • Production simulation with transmission representation using synchronized data National Renewable Energy Laboratory Innovation for Our Energy Future

35. Wind forecasting and scheduling • Analysis on the relative cost/benefit of storage and alternatives that can provide flexibility • Other studies find multiple potential solutions • Modeling: careful specification of physical performance and economics • May result in multiple unit response • Other systems’ results show spreading variability over multiple units is optimal National Renewable Energy Laboratory Innovation for Our Energy Future

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37. Dispatch/control responsibility • Evaluate institutional constraints and the economics of alleviating them • Multiple approaches are possible • Dynamic scheduling (ACE, generation, etc) • Coordinated dispatch • Ad-hoc bi-lateral (tri-lateral) “Craig’s list” for imbalance/energy • More formalized imbalance market (assuming uncoordinated unit commitment) • Fully coordinated commitment and dispatch: combined operation or market • Operating at 5-minute intervals • Other forms of cooperation may be useful • Analysis of options, informed by data National Renewable Energy Laboratory Innovation for Our Energy Future

38. Inefficiency of hydro/thermal • Focus on *total* fuel burn/MWh • Total emissions • Wind saves fuel, but may cause marginal inefficiencies • This must be quantified using high-fidelity simulation that can resolve unit heat rates, etc. National Renewable Energy Laboratory Innovation for Our Energy Future

39. Role of storage • Storage is a flexible resource • Other flexible resources exist • Institutional • Aeroderivative gas turbines • Reciprocating engines • Markets • Advanced scheduling protocols • Load response • Storage time frame: • Regulation (fly-wheel) • Load following (pumped hydro, battery) • Scheduling (pumped hydro, battery) National Renewable Energy Laboratory Innovation for Our Energy Future

40. Gas nominations • Issue: wind forecast and load forecast errors may be costly relative to gas nominations • Gas penalties may result • How to evaluate? • Time-synchronized load/wind data • Power system simulation • Assess impact: similar to imbalance (forecast errors): time-dependent and variable range • Potential for additional gas storage • Alleviate existing problems with gas supply unrelated to wind • Known technology • Fuel hedging and arbitrage (Xcel integration study) National Renewable Energy Laboratory Innovation for Our Energy Future

41. Frequency, inertia, and stability • LVRT common in modern wind turbines • Impact on small power system • Inertia may be an issue – analysis is warranted • Acquire wind turbines with inertia capability • Stability can also be evaluated National Renewable Energy Laboratory Innovation for Our Energy Future

42. Balancing Area Cooperation: What Analyses/Experiments are Underway? • Virtual consolidation • NTTG’s ADI • Possible expansion to load-following time scale • Activity in the NW includes BPA’s ‘feed-forward’ AGC concept • Dynamic scheduling system • ITAP: inter-hour transaction accelerator platform • (nttg.biz) National Renewable Energy Laboratory Innovation for Our Energy Future

43. Other Flexibility Options • Fast-ramping generation with good heat rates, low turn-down, low start-up cost • Bi-lateral pooling agreements (similar to ADI but longer time frames) • Innovation in hydro scheduling • Economic wind curtailment, ramp limitations during critical periods • Morning load pickup • Evening load drop off • Storage has value, but not currently cost-effective and always as a system resource, not for balancing individual loads or generators • Maximize the capacity value of existing conventional generators including hydro resources by taking fullest advantage of wind as a fuel and water saver. National Renewable Energy Laboratory Innovation for Our Energy Future

44. Questions? National Renewable Energy Laboratory Innovation for Our Energy Future