Proceedings of the 5th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2023, December 8–10, 2023, Guangzhou, China

Research Article

Refined Resource Allocation Algorithm for Power Trading Centers Based on User Service Needs

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  • @INPROCEEDINGS{10.4108/eai.8-12-2023.2344797,
        author={Na  Cai and Shuibing  Zheng and Shouquan  Luo and Hang  Gao and Danqi  Chen},
        title={Refined Resource Allocation Algorithm for Power Trading Centers Based on User Service Needs},
        proceedings={Proceedings of the 5th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2023, December 8--10, 2023, Guangzhou, China},
        publisher={EAI},
        proceedings_a={MSIEID},
        year={2024},
        month={4},
        keywords={power trading; refinement of resources;user needs},
        doi={10.4108/eai.8-12-2023.2344797}
    }
    
  • Na Cai
    Shuibing Zheng
    Shouquan Luo
    Hang Gao
    Danqi Chen
    Year: 2024
    Refined Resource Allocation Algorithm for Power Trading Centers Based on User Service Needs
    MSIEID
    EAI
    DOI: 10.4108/eai.8-12-2023.2344797
Na Cai1,*, Shuibing Zheng1, Shouquan Luo1, Hang Gao1, Danqi Chen1
  • 1: Kunming Power Exchange Center Co., Ltd.
*Contact email: yncaina@126.com

Abstract

In order to understand the refined resource allocation algorithm for power trading centers, a research on a refined resource allocation algorithm for power trading centers that is oriented towards user service needs has been proposed. Firstly, distinguish the nodes in the electricity market into two types of entities: energy nodes and energy block proxy routers; Subsequently, preferences in energy supply and demand are divided into three categories based on historical energy supply habits: environmentally friendly, transmission resource saving, and economically efficient; Furthermore, a class of energy information matching algorithms and comprehensive evaluation functions are proposed to meet the optimal allocation of power resources in a multi user environment. Simulation experiments show that this method can increase the proportion of clean energy consumption in market transactions, promote energy consumption nearby, and improve the resource allocation capacity of the power grid.