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Home > Archive>Volume 13, Issue 2, 2025 >650-662. DOI:10.35833/MPCE.2024.000264
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A Clearing Mechanism with Reduced Computational Complexity for Spot Flexibility Markets
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Affiliation:

1.Department of Electrical and Computer Engineering, University of Quebec at Trois-Rivières, Trois-Rivières, Canada;2.Department of Mechanical Engineering, University of Quebec at Trois-Rivières, Trois-Rivières, Canada;3.Laboratoire des Technologies de l’Énergie, Institut de Recherche Hydro-Québec, Shawinigan, Canada

Fund Project:

The authors would like to thank the Laboratoire des Technologies de l’énergie d’Hydro-Québec, the Natural Science and Engineering Research Council of Canada, and the Foundation of Université du Québec à Trois-Rivières.

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    Abstract:

    The spot flexibility markets are before the real-time energy exchange, allowing demand-side management to reduce energy consumption during peak periods. In these markets, demand aggregators must quickly choose the customers ’reduction bids that fulfill grid requirements. This clearing procedure is challenging due to the computational complexity of selecting the optimal bids. Therefore, developing a clearing mechanism that avoids searching the entire flexibility bid space while respecting grid constraints is essential for the smooth operation of the spot flexibility market. This paper presents a clearing mechanism with reduced computational complexity of the winner determination problem in spot flexibility market for demand aggregators carrying out reductions in energy consumption. The proposed approach transforms customers’flexibility bids into a reward-based function. Afterward, the gradient-based optimization solves the bid selection problem. This approach helps demand aggregators achieve satisfactory energy reductions within an appropriate delay for spot flexibility markets. A comparative study presents the effectiveness of the proposed approach against commonly used approaches: hybrid particle swarm optimization genetic algorithm and combinatorial search.

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History
  • Received:March 19,2024
  • Revised:June 14,2024
  • Online: March 26,2025

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