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A simple way to integrate distributed storage into a wholesale electricity market

Author

Listed:
  • Alberto J. Lamadrid

    (Lehigh University)

  • Hao Lu

    (Independent Electricity System Operator (IESO))

  • Timothy D. Mount

    (Cornell University)

Abstract

Current plans to decarbonize the electric supply system imply that the generation from wind and solar sources will grow substantially. This growth will increase the uncertainty of system operations due to the inherent variability of these renewable sources, and as a result, more reserve capacity will be required to provide the ramping (flexibility) needed for reliable operations. This paper assumes that all of the increased uncertainty comes from wind farms on the grid, and it shows how distributed storage managed locally by aggregators can provide the ramping needed without introducing a separate market for flexibility. This can be accomplished when the aggregators minimize the expected daily cost of the energy purchased from the grid for their customers by submitting optimal bids into the wholesale market with high and low price thresholds for discharging and charging the storage. This model is illustrated using a stochastic multi-period security constrained optimal power flow together with realistic data for a reduction of the network in the Northeast Power Coordinating Council region of the United States. The results show that the bidding strategy for distributed storage provides ramping to the grid just as effectively as storage managed by a system operator.

Suggested Citation

  • Alberto J. Lamadrid & Hao Lu & Timothy D. Mount, 2024. "A simple way to integrate distributed storage into a wholesale electricity market," Journal of Regulatory Economics, Springer, vol. 65(1), pages 27-63, June.
  • Handle: RePEc:kap:regeco:v:65:y:2024:i:1:d:10.1007_s11149-023-09467-w
    DOI: 10.1007/s11149-023-09467-w
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    References listed on IDEAS

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    More about this item

    Keywords

    Market design and Intermittent variable renewable energy sources; Markov decision process; Energy storage systems;
    All these keywords.

    JEL classification:

    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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