Electronic Science and Technology ›› 2025, Vol. 38 ›› Issue (5): 1-7.doi: 10.16180/j.cnki.issn1007-7820.2025.05.001

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Two-Stage Stochastic Programming of Active Distribution Network Considering SOP and Active Voltage Control

LIU Aiwang1(), ZHANG Mingming1, YAO Baoming1, HU Chengping1, JIANG Zhenyu1, ZHANG Chao1, SHI Yunhui2   

  1. 1. Haiyan County Power Supply Company,State Grid Zhejiang Electric Power Co., LTD.,Jiaxing 314399,China
    2. College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China
  • Received:2023-10-16 Revised:2023-11-12 Online:2025-05-15 Published:2025-05-14
  • Contact: LIU Aiwang E-mail:385199092@qq.com
  • Supported by:
    National Natural Science Foundation of China(52007173)

Abstract:

In order to solve the problem of insufficient carrying capacity of the distribution network for new energy, this study proposes a joint planning model and solution method considering SOP(Soft Open Point) and active load voltage control. The SOP mathematical model applied to distribution network planning is established, and the linear model is established for the load voltage characteristics in polynomial form and exponential form respectively. A two-stage stochastic second-order cone programming model for active distribution network is established with the objective of distributed new energy carrying capacity, investment cost and operation cost to determine the location, capacity and intraday operating strategy of devices including SOP, capacitors and distributed energy sources.Considering the uncertainty of new energy, load and energy price, a scene clustering method based on K-means is proposed. An improved Benders decomposition algorithm is proposed to solve the proposed model. The validity and correctness of the proposed model are verified by the improved 51-node system, and the influence of SOP and active voltage control on the carrying capacity of new energy is analyzed.

Key words: soft switching, active voltage control, load voltage characteristics, random programming, photovoltaic bearing capacity, second-order cone programming, trusted region method, Benders decomposition

CLC Number: 

  • TP202