1 / 34

Integrating wind resources: siting decisions in the Midwest

Integrating wind resources: siting decisions in the Midwest. Julian Lamy (speaker) Ines Azevedo Paulina Jaramillo. The Midwest has ambitious renewable targets. Illinois RPS: 25% by 2025, 60 to 75% from wind 30 TWh (10 GW) of wind needed for this target

zaynah
Download Presentation

Integrating wind resources: siting decisions in the Midwest

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Integrating wind resources: siting decisions in the Midwest Julian Lamy (speaker) Ines Azevedo Paulina Jaramillo

  2. The Midwesthas ambitious renewable targets • Illinois RPS: 25% by 2025, 60to 75% from wind • 30 TWh (10 GW) of wind needed for this target • RPSs in MN, MO, WI, and MIadd another 30 TWh (10 GW) • Currently MISO has about 10 GW • Research question: in an ideal world, if we could choose to build the farms anywhere in MISO, where would we build them? • What metrics to consider?

  3. Annual average capacity factor EWITS (2012), 2006

  4. Variability is also a big concern, even for the highest capacity resources

  5. Coefficient of Variation (CoV) in hourly output EWITS (2012), 2006

  6. Transmission: hard to say… MTEP 2012, pg. 49

  7. Data on available existing transmission capacity is limited, what about generation? 17% 22% 61% 26% (eGRID, 2012), % of generation in 2009 by area

  8. Past research suggests that building around Illinois is best • Hoppock and Patiño-Echeverri (2010) • Evaluated wind farms using capacity factors for hypothetical sites using EWITS data (2008) • Remote wind farms were required to build transmission lines for delivery to Illinois (with sensitivities) • This paper add to the literature by: • In addition to capacity factors, we include a metric to account for the temporal variability of each farm using a simple dispatch model • Delivery must be to some node cluster within MISO, not necessarily to Illinois

  9. Modeling Approach Generation cost for each non-wind generator (i) ramp cost for each non-wind generator (i) Capital costs incurred for each wind farm Ramp cost ($/MWh) incurred by non-wind generator i Annualized wind capital cost + annualized transmission capital cost marginal gen cost for non-wind generator i Change in generation from hour (t-1) to t Generation in hour t by non-wind generator i Binary variable : b=1: build farm k b=0: don’t build farm k

  10. Modeling Approach Generation cost for each non-wind generator (i) ramp cost for each non-wind generator (i) Capital costs incurred for each wind farm Market Clearing (wind “must-run”) Annual wind generation target Generator capacity and ramp limits

  11. Assumptions: Ramping Cost • DeCarolis and Keith (2006) • Increasing wind power to serve 50% of demand adds about $10-20/MWh due to intermittency + transmission costs • Lueken et al. (2012) • Analyzed the variability of 20 wind farms in ERCOT over one year and concluded that costs due to variability are on average $4/MWh • Hirst(2001) • 100 MW wind farm in MN for delivery to PJM • Intra-hour balance cost: $7 to 28/MWh • regulation costs: $5 to $30/MWh • Very uncertain so we used a parametric analysis and tested the sensitivity to the results: • $0, $5, $10, $30, and $100/MWh • Incurred during hourly changes in dispatchable generation

  12. Transmission Assumptions Costs Distance required per site x To account for additional transmission needed along the grid: 100%, 200%, 300%, 400%

  13. Selection of transmission node clusters MISO LMP map, accessed July 3, 2013 https://www.misoenergy.org/MarketsOperations/RealTimeMarketData/Pages/LMPContourMap.aspx

  14. MISO Delivery $1,000/ MW-km - 200% - $10/MWh

  15. MISO Delivery $1,000/ MW-km - 200% - $10/MWh ~ 50 km each from node cluster ~ 10 km from node cluster How does the answer change under different ramping cost assumptions?

  16. MISO Delivery - $1,000/ MW-km – 200% % of total MW built ~8 GW built in MISO

  17. Summary of Scenarios Considered

  18. Conclusions • In most scenarios, remote wind is optimal even when not accounting for variability($0/MWh) • When ramping costs ≥$10/MWh, the optimal portfolio of wind farm locations changes

  19. Next Steps • Refine scenario to better represent the necessary transmission capacity to connect farms to MISO’s grid • MISO’s historical Impact Studies • Find someone with a detailed dispatch/ power flow model …unlikely but I’m hopeful… • Other ideas?? • Better represent transmission capacity needs within Illinois. Currently, assume that 0 km need to be built

  20. Acknowledgements This work was supported by the center for Climate and Energy Decision Making (SES-0949710), through a cooperative agreement between the National Science Foundation and Carnegie Mellon University, and by the RenewElec project.

  21. Appendix

  22. MISO Delivery - $1,000/ MW-km – 100% ~8 GW built in MISO

  23. MISO Delivery - $1,000/ MW-km – 300% ~8 GW built in MISO

  24. MISO Delivery - $1,000/ MW-km – 400% ~8 GW built in MISO

  25. Illinois Delivery - $1,000/ MW-km – 100% ~8 GW built in MISO

  26. Illinois Delivery - $1,000/ MW-km – 50% ~8 GW built in MISO

  27. Different sites within Illinois are chosen! Red represent < 100% capacity of the wind farm was built (i.e., 0 < bk <1) Strange pattern likely because of optimal “grouping” of farms to decrease variability

  28. Assumptions: Dispatchable Generators • Nuclear, hydro, and existing wind are “must-run” • Gas + Coal are aggregated into one representative dispatchable unit • Model has to dispatch 1 generator to support the new wind i: includes residual fuel oil, biomass, and other generation ii: wind data from MISO ( 2012a) iii: total load data is from MISO (201b) iv: not currently included, scenarios to be included in final report v: Computed using $/mmbtu from AEO (2013), and mmbtu/kwh from EGrid (2009)

  29. Conclusions • MISO delivery scenarios • In most scenarios, remote wind is optimal even when not accounting for variability($0/MWh) • When ramping costs ≥$10/MWh, the optimal portfolio of wind farm locations changes • Illinois delivery scenarios • Probably too pessimistic for remote wind • For 100% transmission case, Illinois is always optimal • For the 50% transmission case, adjoining states such as MO and IA are competitive when ramping costs ≥ $30/MWh • Even with Illinois only wind development, accounting for ramping costs ≥ $30/MWhaffects siting within Illinois

  30. Xcel Energy RFP

  31. Impact Study Assessment for ND

  32. Box Plots of CF and COV by region Remote ND, SD, MN, NE Local IL, IN, IA, MO Remote ND, SD, MN, NE Local IL, IN, IA, MO Lakes MI, WI Lakes MI, WI

  33. Existing Generators in MISO (eGRID, 2012)

  34. 300% 100% 100% 200% 400% Ramping Cost Assumptions ($/MWh)

More Related