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Operating peer-to-peer electricity markets under uncertainty via learning-based, distributed optimal control

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  • Tsaousoglou, Georgios
  • Ellinas, Petros
  • Varvarigos, Emmanouel

Abstract

Towards the global endeavor of clean energy transition, there is a rapid development of distributed energy resources installed in the premises of residential or commercial users, enabling them to act as flexible energy prosumers. Empowering prosumers is envisioned as a catalytic development for modern energy economies, with recent research, as well as innovation and policy actions, pointing to the promising direction of decentralized energy markets, where active energy prosumers exchange energy in a decentralized fashion. Despite the vast amount of recent research on prosumer-centric peer-to-peer (p2p) energy markets, only a small subset of studies accounts for managing the inherent uncertainty of prosumers’ flexible demands.

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  • Tsaousoglou, Georgios & Ellinas, Petros & Varvarigos, Emmanouel, 2023. "Operating peer-to-peer electricity markets under uncertainty via learning-based, distributed optimal control," Applied Energy, Elsevier, vol. 343(C).
    • Handle: RePEc:eee:appene:v:343:y:2023:i:c:s0306261923005986
    DOI: 10.1016/j.apenergy.2023.121234
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    References listed on IDEAS

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    1. Yu, Liying & Wang, Peng & Chen, Zhe & Li, Dewen & Li, Ning & Cherkaoui, Rachid, 2023. "Finding Nash equilibrium based on reinforcement learning for bidding strategy and distributed algorithm for ISO in imperfect electricity market," Applied Energy, Elsevier, vol. 350(C).

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