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Estimating the value of wind energy using electricity locational marginal price

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  • Lewis, Geoffrey McD.

Abstract

There is an increasing interest in adding renewables such as wind to electricity generation portfolios in larger amounts as one response to concern about atmospheric carbon emissions from our energy system and the resulting climate change. Most policies with the aim of promoting renewables (e.g., RPS, FIT) do not explicitly address siting issues, which for wind energy are currently approached as the intersection of wind resource, land control, and transmission factors. This work proposes the use of locational marginal price (LMP), the location and time specific cost of electricity on the wholesale market, to signal locations where generation can address electricity system insufficiency. After an examination of the spatial and temporal behavior of LMP in Michigan over the first two years of wholesale market operation, this work combines LMP with wind speed data to generate a value metric. High value sites in Michigan tend to be sites with higher wind speeds, with the bulk of value accruing in the fall and winter seasons.

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  • Lewis, Geoffrey McD., 2010. "Estimating the value of wind energy using electricity locational marginal price," Energy Policy, Elsevier, vol. 38(7), pages 3221-3231, July.
    • Handle: RePEc:eee:enepol:v:38:y:2010:i:7:p:3221-3231
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    Cited by:

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    2. Calvert, K. & Pearce, J.M. & Mabee, W.E., 2013. "Toward renewable energy geo-information infrastructures: Applications of GIScience and remote sensing that build institutional capacity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 416-429.
    3. Hirth, Lion & Müller, Simon, 2016. "System-friendly wind power," Energy Economics, Elsevier, vol. 56(C), pages 51-63.
    4. Richard Schmalensee, 2013. "The Performance of U.S. Wind and Solar Generating Units," NBER Working Papers 19509, National Bureau of Economic Research, Inc.
    5. Brandstätt, Christine & Brunekreeft, Gert & Friedrichsen, Nele, 2011. "Locational signals to reduce network investments in smart distribution grids: What works and what not?," Utilities Policy, Elsevier, vol. 19(4), pages 244-254.
    6. Eising, Manuel & Hobbie, Hannes & Möst, Dominik, 2020. "Future wind and solar power market values in Germany — Evidence of spatial and technological dependencies?," Energy Economics, Elsevier, vol. 86(C).
    7. Odeh, Rodrigo Pérez & Watts, David, 2019. "Impacts of wind and solar spatial diversification on its market value: A case study of the Chilean electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 442-461.
    8. He, Fang & Wu, Di & Yin, Yafeng & Guan, Yongpei, 2013. "Optimal deployment of public charging stations for plug-in hybrid electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 47(C), pages 87-101.
    9. Lamy, Julian V. & Jaramillo, Paulina & Azevedo, Inês L. & Wiser, Ryan, 2016. "Should we build wind farms close to load or invest in transmission to access better wind resources in remote areas? A case study in the MISO region," Energy Policy, Elsevier, vol. 96(C), pages 341-350.
    10. Christoph M. Flath & Jens P. Ilg & Sebastian Gottwalt & Hartmut Schmeck & Christof Weinhardt, 2014. "Improving Electric Vehicle Charging Coordination Through Area Pricing," Transportation Science, INFORMS, vol. 48(4), pages 619-634, November.
    11. Bernath, Christiane & Deac, Gerda & Sensfuß, Frank, 2021. "Impact of sector coupling on the market value of renewable energies – A model-based scenario analysis," Applied Energy, Elsevier, vol. 281(C).
    12. Kung, Harold H., 2012. "Impact of deployment of renewable portfolio standard on the electricity price in the State of Illinois and implications on policies," Energy Policy, Elsevier, vol. 44(C), pages 425-430.
    13. Hirth, Lion & Ueckerdt, Falko & Edenhofer, Ottmar, 2015. "Integration costs revisited – An economic framework for wind and solar variability," Renewable Energy, Elsevier, vol. 74(C), pages 925-939.
    14. Chun-Yao Lee & Chang-En Wu, 2020. "Short-Term Electricity Price Forecasting Based on Similar Day-Based Neural Network," Energies, MDPI, vol. 13(17), pages 1-15, August.
    15. Lion Hirth, Falko Ueckerdt, and Ottmar Edenhofer, 2016. "Why Wind Is Not Coal: On the Economics of Electricity Generation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    16. Kirkerud, Jon Gustav & Bolkesjø, Torjus Folsland & Trømborg, Erik, 2017. "Power-to-heat as a flexibility measure for integration of renewable energy," Energy, Elsevier, vol. 128(C), pages 776-784.
    17. Baer, Paul & Brown, Marilyn A. & Kim, Gyungwon, 2015. "The job generation impacts of expanding industrial cogeneration," Ecological Economics, Elsevier, vol. 110(C), pages 141-153.

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