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A pool-based energy market model for microgrids characterized by scheduled blackouts

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  • Sawwas, Ahmad
  • Chedid, Riad

Abstract

This paper proposes a novel pool-based energy market platform suitable for developing countries where electric utilities suffer from the lack of sufficient generation capacities. To compensate for the electric utility outages, diesel generators are considered as primary sources of energy. However, diesel generators are quite polluting and expensive. Therefore, the objectives of the proposed market are to reduce reliance on both the diesel generators and the grid during peak hours, increasing the contribution of clean energy technologies within the distribution network and achieving profitability for all participants.The proposed market is based on the interaction of three main players: the distribution system operator, the microgrid community agent and the microgrid/load agent. Multiple sequential optimization problems are formulated to accomplish the market objectives, and solutions are sought through genetic algorithm, dynamic programming energy management algorithm, and interior point algorithm.The implementation of the proposed market, compared to independent market operation, results in further reduction in diesel generators power supply, almost completeutilizationof excess photovoltaic energy, elimination of energy shortages, and cutting down of all participants’ annual operating costs.

Suggested Citation

  • Sawwas, Ahmad & Chedid, Riad, 2021. "A pool-based energy market model for microgrids characterized by scheduled blackouts," Applied Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:appene:v:283:y:2021:i:c:s0306261920317384
    DOI: 10.1016/j.apenergy.2020.116358
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    References listed on IDEAS

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    1. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
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    Cited by:

    1. Hassani, Hossein & Razavi-Far, Roozbeh & Saif, Mehrdad, 2022. "Real-time out-of-step prediction control to prevent emerging blackouts in power systems: A reinforcement learning approach," Applied Energy, Elsevier, vol. 314(C).
    2. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Hannes Agabus, 2023. "Market Mechanisms and Trading in Microgrid Local Electricity Markets: A Comprehensive Review," Energies, MDPI, vol. 16(5), pages 1-52, February.

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