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Operation Optimization Method of Distribution Network with Wind Turbine and Photovoltaic Considering Clustering and Energy Storage

Author

Listed:
  • Fangfang Zheng

    (College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang 110866, China)

  • Xiaofang Meng

    (College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang 110866, China)

  • Lidi Wang

    (College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang 110866, China)

  • Nannan Zhang

    (College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang 110866, China)

Abstract

The problem of distribution network operation optimization is diversified and uncertain. In order to solve this problem, this paper proposes a method of distribution network operation optimization considering wind-solar clustering, which includes source load and storage. Taking the total operating cost as the objective function, it includes network loss cost, unit operating cost, and considers a variety of constraints such as energy storage device constraints and demand response constraints. This paper aims to optimize the operation according to different wind-solar clustering scenes to improve the economy of distribution network. Taking the 365-day wind-solar output curves as the research object, K-means clustering is carried out, and the best k value is obtained by elbow rule. The second-order cone programming method and solver are used to solve the optimization model of each typical scenario, and the operation optimization analysis of each typical scenario obtained by clustering is carried out. Taking IEEE33 system and local 365-day wind-solar units output scenes as examples, the period is 24 h, which verifies the effectiveness of the proposed method. The proposed method has guiding significance for the operation optimization of distribution network.

Suggested Citation

  • Fangfang Zheng & Xiaofang Meng & Lidi Wang & Nannan Zhang, 2023. "Operation Optimization Method of Distribution Network with Wind Turbine and Photovoltaic Considering Clustering and Energy Storage," Sustainability, MDPI, vol. 15(3), pages 1-22, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2184-:d:1045624
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    References listed on IDEAS

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    1. Hamza Mubarak & Munir Azam Muhammad & Nurulafiqah Nadzirah Mansor & Hazlie Mokhlis & Shameem Ahmad & Tofael Ahmed & Muhammad Sufyan, 2022. "Operational Cost Minimization of Electrical Distribution Network during Switching for Sustainable Operation," Sustainability, MDPI, vol. 14(7), pages 1-23, April.
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    Cited by:

    1. Chen, Youliang & Huang, Xiaoguang & Li, Wei & Fan, Rong & Zi, Pingyang & Wang, Xin, 2023. "Application of deep learning modelling of the optimal operation conditions of auxiliary equipment of combined cycle gas turbine power station," Energy, Elsevier, vol. 285(C).
    2. Xuya Zhang & Yue Wang & Dongqing Zhang, 2024. "Location-Routing Optimization for Two-Echelon Cold Chain Logistics of Front Warehouses Based on a Hybrid Ant Colony Algorithm," Mathematics, MDPI, vol. 12(12), pages 1-22, June.
    3. Fangfang Zheng & Xiaofang Meng & Tiefeng Xu & Yongchang Sun & Nannan Zhang, 2023. "Voltage Zoning Regulation Method of Distribution Network with High Proportion of Photovoltaic Considering Energy Storage Configuration," Sustainability, MDPI, vol. 15(13), pages 1-19, July.

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