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Distributed model-free optimisation in community-based energy market

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  • Houman Asgari
  • Maryam Babazadeh

Abstract

A distributed data-driven algorithm is proposed for market clearing within a community-based energy market. The objective is to maximise social welfare in energy trading. Each participant in the market, known as a prosumer, employs an extremum-seeking control (ESC) algorithm within a consensus-based architecture based on simple third-order dynamics. The proposed method circumvents the need for a central coordinator in the market clearing process. Furthermore, prosumers do not require analytical and exact formulations of cost or utility functions. They are required to transmit only a single local decision variable to the neighbours through an undirected connected graph. Under the assumption that prosumers have strongly convex local objective functions, the proposed algorithm demonstrates semi-global practical asymptotic (SPA) convergence to the optimal solution. This convergence is established using averaging theory. Simulation results validate the effectiveness, scalability, and robustness of the proposed distributed strategy.

Suggested Citation

  • Houman Asgari & Maryam Babazadeh, 2025. "Distributed model-free optimisation in community-based energy market," International Journal of Systems Science, Taylor & Francis Journals, vol. 56(12), pages 3098-3113, September.
    • Handle: RePEc:taf:tsysxx:v:56:y:2025:i:12:p:3098-3113
    DOI: 10.1080/00207721.2025.2469151
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