Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2–4, 2023, Nanchang, China

Research Article

The Two-layer Optimization Model Design of "Source-Network-Charge-Storage" Coordination for a New Power System Considering Integrated Cost

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  • @INPROCEEDINGS{10.4108/eai.2-6-2023.2334665,
        author={Yuheng  Sha and Qian  Ma and Chao  Xu and Xue  Tan and Jun  Yan and Jing  Zhang and Tingting  Li},
        title={The Two-layer Optimization Model Design of "Source-Network-Charge-Storage" Coordination for a New Power System Considering Integrated Cost},
        proceedings={Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2--4, 2023, Nanchang, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2023},
        month={8},
        keywords={"source-net-load-storage" collaboration; two-layer optimization model; quantum genetic algorithm},
        doi={10.4108/eai.2-6-2023.2334665}
    }
    
  • Yuheng Sha
    Qian Ma
    Chao Xu
    Xue Tan
    Jun Yan
    Jing Zhang
    Tingting Li
    Year: 2023
    The Two-layer Optimization Model Design of "Source-Network-Charge-Storage" Coordination for a New Power System Considering Integrated Cost
    ICIDC
    EAI
    DOI: 10.4108/eai.2-6-2023.2334665
Yuheng Sha1, Qian Ma2, Chao Xu2, Xue Tan3, Jun Yan4, Jing Zhang4,*, Tingting Li4
  • 1: State Grid Corporation of China
  • 2: State Grid Jiangsu Electric Power Co., Ltd.
  • 3: State Grid Energy Research Institute Co., Ltd.
  • 4: Tianjin Tianda Qiushi Power New Technology Co., Ltd.
*Contact email: ShaYuheng2022@126.com

Abstract

The widespread adoption of renewable energy plays a crucial role in achieving the Sustainable Development Goals of a low carbon power system. To effectively manage and control the distribution network system and promote integrated coordination, a two-layer optimization model is proposed. This model is based on the coordination of "source-network-charge-storage" within the framework of the new power system. With the lowest annual integrated cost as the upper optimization objective and the optimal load variation as the lower optimization objective, quantum genetic algorithm was used to conduct simulation analysis, and the results showed that the model proposed in this paper could not only save the integrated cost of active distribution network, but also improve the proportion of new energy consumption and improve the comprehensive benefits of distribution network system.