Electric Power ›› 2025, Vol. 58 ›› Issue (1): 85-92.DOI: 10.11930/j.issn.1004-9649.202405027

• Data-driven Analysis and Control of Power System Security and Stability • Previous Articles     Next Articles

Multi-objective Optimization Control Strategy for Soft Open Point in Distribution Network with High Penetration of DG

Wenjun LIU1,2(), Weijie DONG3(), Yuanyang CHEN4, Shuyun HE1,2, Jian CHEN1,2, Dongqiang JIA5   

  1. 1. State Grid Hunan Electric Power Company Limited Economic & Technical Research Institute, Changsha 410007, China
    2. Hunan Key Laboratory of Energy Internet Supply-demand and Operation, Changsha 410007, China
    3. Beijing University of Information Technology, College of Mechanical and Electrical Engineering, Beijing 100192, China
    4. State Grid Hunan Electric Power Company Limited, Changsha 410004, China
    5. State Grid Beijing Electric Power Company, Beijing 100031, China
  • Received:2024-05-09 Accepted:2024-08-07 Online:2025-01-23 Published:2025-01-28
  • Supported by:
    This work is supported by National Natural Science Foundation of China (No.52237008), Science and Technology Project of State Grid Hunan Electric Power Co., Ltd. (No.5216A222000S).

Abstract:

A multi-objective optimization control strategy for distribution station SOP is proposed to enhance the distributed generation (DG) consumption capability of the distribution network by utilizing multi soft open point (SOP). By analyzing the access mode of SOP in the distribution network and considering its role in distributed power consumption and peak shaving, a multi-objective model was constructed to maximize the daily consumption of distributed energy, minimize control costs, and minimize the deviation of daily net load of feeder lines. Conduct simulation comparison and verification using an improved distribution network example. The results indicate that SOP integration is beneficial for improving the consumption of new energy and achieving load balancing.

Key words: soft open point, distribution network, distributed estimation, multi-objective optimization