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Effects of aggregating electric load in the United States

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  • Corcoran, Bethany A.
  • Jenkins, Nick
  • Jacobson, Mark Z.

Abstract

This study quantifies the effects of aggregating electric load over various combinations (Aggregation Groupings) of the 10 Federal Energy Regulatory Commission (FERC) regions in the contiguous U.S. Generator capacity capital cost savings, load energy shift operating cost savings, reserve requirement cost savings, and transmission costs due to aggregation were calculated for each Aggregation Grouping. Eight scenarios of Aggregation Groupings over the U.S. were formed to estimate overall system cost. Transmission costs outweighed cost savings due to aggregation for all scenarios and nearly all Aggregation Groupings. East–west transmission layouts had the highest overall cost, and interconnecting ERCOT to adjacent FERC Regions resulted in increased costs, both due to limited existing transmission capacity. This study found little economic benefit of aggregating electric load alone (e.g., without aggregating renewable generators simultaneously), except in the West and Northwest U.S. If aggregation of load alone is desired, small, regional consolidations yield the lowest overall cost. This study neither examines nor precludes benefits of interconnecting geographically-dispersed renewable generators with load. It also does not consider effects from sub-hourly load variability, fuel diversity and price uncertainty, energy price differences due to congestion, or uncertainty due to forecasting errors; thus, results are valid only for the assumptions made.

Suggested Citation

  • Corcoran, Bethany A. & Jenkins, Nick & Jacobson, Mark Z., 2012. "Effects of aggregating electric load in the United States," Energy Policy, Elsevier, vol. 46(C), pages 399-416.
  • Handle: RePEc:eee:enepol:v:46:y:2012:i:c:p:399-416
    DOI: 10.1016/j.enpol.2012.03.079
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    References listed on IDEAS

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    Cited by:

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    2. Jafari-Marandi, Ruholla & Hu, Mengqi & Omitaomu, OluFemi A., 2016. "A distributed decision framework for building clusters with different heterogeneity settings," Applied Energy, Elsevier, vol. 165(C), pages 393-404.
    3. Karl-Kiên Cao & Kai von Krbek & Manuel Wetzel & Felix Cebulla & Sebastian Schreck, 2019. "Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models," Energies, MDPI, vol. 12(24), pages 1-51, December.
    4. Becker, Sarah & Frew, Bethany A. & Andresen, Gorm B. & Zeyer, Timo & Schramm, Stefan & Greiner, Martin & Jacobson, Mark Z., 2014. "Features of a fully renewable US electricity system: Optimized mixes of wind and solar PV and transmission grid extensions," Energy, Elsevier, vol. 72(C), pages 443-458.
    5. Frew, Bethany A. & Becker, Sarah & Dvorak, Michael J. & Andresen, Gorm B. & Jacobson, Mark Z., 2016. "Flexibility mechanisms and pathways to a highly renewable US electricity future," Energy, Elsevier, vol. 101(C), pages 65-78.
    6. Rodríguez, Rolando A. & Becker, Sarah & Andresen, Gorm B. & Heide, Dominik & Greiner, Martin, 2014. "Transmission needs across a fully renewable European power system," Renewable Energy, Elsevier, vol. 63(C), pages 467-476.
    7. Becker, Sarah & Frew, Bethany A. & Andresen, Gorm B. & Jacobson, Mark Z. & Schramm, Stefan & Greiner, Martin, 2015. "Renewable build-up pathways for the US: Generation costs are not system costs," Energy, Elsevier, vol. 81(C), pages 437-445.
    8. Deason, Wesley, 2018. "Comparison of 100% renewable energy system scenarios with a focus on flexibility and cost," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3168-3178.

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