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Impact of imperfect foresight on the optimal DER deployment, remuneration and policy

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  • Kim, Jip
  • Bialek, Sylwia
  • Ünel, Burçin
  • Dvorkin, Yury

Abstract

This paper proposes a decision-making framework to optimize electricity tariffs and remuneration policy for renewable energy sources operating in transmission- and distribution-level (T&D) marketplaces. We develop perfect and imperfect foresight models with a multi-level structure to investigate the effects of the inability of actors to correctly predict future remuneration on the efficiency of the decisions made by policymakers. The important advantage of the proposed models is that while they are capturing conflicting interests and different information availability of stakeholders involved, they also account for techno-economic constraints on operations of generation, transmission and distribution assets. The presented models can accommodate net metering, value stack, and distribution locational marginal price (DLMP)-based remuneration policies, which allows for their numerical comparison in terms of the effect on the optimal roll-out of distributed energy resources (DERs). The case study carried out for the NYISO and Manhattan T&D networks reveals that inaccurate foresight on the DER remuneration diminishes the social welfare under all DER remuneration policies, with the maximum loss of 1.6% across all considered scenarios.

Suggested Citation

  • Kim, Jip & Bialek, Sylwia & Ünel, Burçin & Dvorkin, Yury, 2022. "Impact of imperfect foresight on the optimal DER deployment, remuneration and policy," Applied Energy, Elsevier, vol. 326(C).
    • Handle: RePEc:eee:appene:v:326:y:2022:i:c:s0306261922011485
    DOI: 10.1016/j.apenergy.2022.119885
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    References listed on IDEAS

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    1. Perez, Richard & Rábago, Karl R. & Trahan, Mike & Rawlings, Lyle & Norris, Ben & Hoff, Tom & Putnam, Morgan & Perez, Marc, 2016. "Achieving very high PV penetration – The need for an effective electricity remuneration framework and a central role for grid operators," Energy Policy, Elsevier, vol. 96(C), pages 27-35.
    2. F. Selin Yanikara & Panagiotis Andrianesis & Michael Caramanis, 2020. "Power Markets with Information-Aware Self-scheduling Electric Vehicles," Dynamic Games and Applications, Springer, vol. 10(4), pages 930-967, December.
    3. Pineda, Salvador & Boomsma, Trine K. & Wogrin, Sonja, 2018. "Renewable generation expansion under different support schemes: A stochastic equilibrium approach," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1086-1099.
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