湖南电力 ›› 2025, Vol. 45 ›› Issue (5): 124-132.doi: 10.3969/j.issn.1008-0198.2025.05.017

• 电力工程建设与应用 • 上一篇    下一篇

基于改进蜣螂算法的分布式电源选址定容方法

周武定1, 张小兵1,2,3, 曾进辉1, 刘颉1, 陈泽文1, 贺宇轩1   

  1. 1.湖南工业大学交通与电气工程学院, 湖南 株洲 412007;
    2.国网湖南省电力有限公司株洲供电分公司, 湖南 株洲 412000;
    3.株洲电力勘测设计科研有限公司, 湖南 株洲 412000
  • 收稿日期:2025-08-12 修回日期:2025-08-20 发布日期:2025-11-11
  • 通信作者: 周武定(2001),男,硕士研究生,研究方向为新能源配置优化。
  • 作者简介:张小兵(1984),男,硕士,从事变电运维管理、输变电工程设计工作。
  • 基金资助:
    国家自然科学基金项目(52377185)

Distributed Power Generation Siting and Sizing Method Based on Improved SCDBO Algorithm

ZHOU Wuding1, ZHANG Xiaobing1,2,3, ZENG Jinhui1, LIU Jie1, CHEN Zewen1, HE Yuxuan1   

  1. 1. School of Transportation and Electrical Engineering, Hunan University of Technology, Zhuzhou 412007, China;
    2. State Grid Zhuzhou Power Supply Company, Zhuzhou 412000, China;
    3. Zhuzhou Electric Power Survey, Design & Research Co., Ltd., Zhuzhou 412000, China
  • Received:2025-08-12 Revised:2025-08-20 Published:2025-11-11

摘要: 针对传统分布式电源选址定容规划中高维非线性问题及备选节点策略难以充分反映配电网实际结构需求的难点,提出一种基于改进蜣螂优化算法的分布式电源选址定容方法。首先,构建融合节点负荷敏感系数的加权有功损耗目标函数,并与电压偏差共同组成双目标优化模型。其次,设计融合Piecewise混沌初始化、随机游走扰动与纵横交叉策略的改进蜣螂优化算法,提升全局搜索能力与复杂环境下的适应性。最后,引用IEEE-33节点配电系统进行算例分析,并引入全生命周期视角,从净收益、投资成本与碳减排效益等方面对优化方案进行经济评估。结果表明,所提方法不仅在降低网损与电压偏差方面优于多种传统算法,而且具备显著的经济优势,验证了所提方法在技术性能与经济可行性方面的综合优越性。

关键词: 分布式电源, 选址定容, 改进蜣螂优化算法, 全生命周期经济效益分析

Abstract: In response to the challenges of high-dimensional nonlinear problems and alternative node strategies that struggle to accurately reflect the actual structural requirements of the distribution network in traditional distributed generation (DG) siting and sizing planning, a DG siting and sizing method based on an improved strategy combined dung beetle optimization algorithm is proposed. Firstly, the weighted active loss objective function incorporating the load sensitivity factor(LSF) of the fusion node is constructed, and the dual-objective optimization model is formed together with the voltage deviation. Secondly, an improved dung beetle optimization algorithm that integrates Piecewise chaotic initialization, random walk perturbation, and cross strategies is designed to enhance global search capabilities and adaptability in complex environments. Finally, through the analysis of the IEEE-33 node distribution system example, a comprehensive evaluation of the optimization scheme is conducted from the perspective of the entire lifecycle, including aspects such as net benefits, investment costs, and carbon reduction benefits. The results indicate that the proposed method not only outperforms various traditional algorithms in reducing network losses and voltage deviations, but also demonstrates significant economic advantages, which validates its comprehensive superiority in both technical performance and economic feasibility.

Key words: distributed power generation, siting and sizing, improved dung beetle optimization algorithm, entire life cycle economic analysis

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