湖南电力 ›› 2025, Vol. 45 ›› Issue (4): 32-38.doi: 10.3969/j.issn.1008-0198.2025.04.006

• 专家专栏:电力防灾减灾 • 上一篇    下一篇

蓄滞洪区域约束下变电站选址GA-PSO混合优化方法

雷川丽1, 罗惠平1, 唐外文2, 何亮3, 李君1, 刘爱军4, 尹迪克5, 刘功杰1   

  1. 1.国网湖南省电力有限公司经济技术研究院,湖南 长沙 410007;
    2.国网湖南省电力有限公司,湖南 长沙 410004;
    3.国网湖南省电力有限公司建设分公司,湖南 长沙 410007;
    4.湖南华晨工程设计咨询有限公司,湖南 长沙 410004;
    5.国网湖南省电力有限公司岳阳供电分公司,湖南 岳阳 430600
  • 收稿日期:2025-04-15 修回日期:2025-06-07 出版日期:2025-08-25 发布日期:2025-09-05
  • 通信作者: 刘爱军(1985),男,本科,高级工程师,研究方向为输变电工程项目管理及设计技术。
  • 作者简介:雷川丽(1979),女,硕士,高级工程师,研究方向为输变电工程项目管理及规划评审技术。
  • 基金资助:
    国网湖南省电力有限公司科技项目(B616A224000J)

GA-PSO Hybrid Optimization Method for Substation Site Selection Under Constraint of Flood Storage and Detention Areas

LEI Chuanli1, LUO Huiping1, TANG Waiwen2, HE Liang3, LI Jun1, LIU Aijun4, YIN Dike5, LIU Gongjie1   

  1. 1. State Grid Hunan Electric Power Company Limited Economic and Technological Research Institute, Changsha 410007, China;
    2. State Grid Hunan Electric Power Company Limited, Changsha 410004, China;
    3. State Grid Hunan Electric Power Company Limited Construction Branch, Changsha 410007, China;
    4. Hunan Huachen Engineering Design and Consulting Co., Ltd., Changsha 410004, China;
    5. State Grid Yueyang Power Supply Company, Yueyang 430600, China
  • Received:2025-04-15 Revised:2025-06-07 Online:2025-08-25 Published:2025-09-05

摘要: 在蓄滞洪区域内变电站选址规划过程中,多源变电站主要采用组合测算实现选址优化,全局搜索效率较低,经济性不足。为此提出一种考虑蓄滞洪区域约束的变电站选址GA-PSO混合优化方法,并开展相关设计与性能分析。通过分析区域水文气象数据,确定选址的低风险区域,并按照区域内的用户电力需求,划定变电站电力负荷密集范围。通过分析水文低风险区域和电力负荷密集区域的重叠情况,确定可计算域,并进行网格划分。将蓄滞洪区域的水文气象作为约束条件,在网格划分处标定多个候选站址,融合GA-PSO算法计算每个候选站址的个体适应度,按照适应度展开选择、交叉、变异等混合优化筛选操作,完成初始选址规划目标。更新初始规划站址的信息与数据,不断训练及迭代,筛选出综合适应度最高的站址作为规划目标,完成选址寻优。实验结果表明:应用所提方法选址后,拟规划的变电站在每个周期的建设耗费成本均被控制在300万元以下,具有较高的经济性。

关键词: 蓄滞洪区域, 变电站, 选址优化, GA-PSO, 供电覆盖, 供电网架

Abstract: In the process of site selection and planning for substations in flood storage and detention areas, multi-source substations mainly use combination calculation to achieve site selection optimization, resulting in low efficiency in global search and insufficient economic efficiency. To this end, a GA-PSO hybrid optimization method for substation site selection considering the constraints of flood storage and detention areas is proposed, and relevant design and performance analysis are carried out. By analyzing regional hydrological and meteorological data, low-risk areas for site selection are determined, and the power load intensive range of substations is delineated according to the electricity demand of users in the area. By analyzing the overlap between areas with low hydrological risk and areas with high power load, the computable domain is determined and grid division is carried out. Taking the hydro meteorological conditions of the flood storage and detention area as constraints, multiple candidate sites are marked at the grid division. The GA-PSO algorithm is integrated to calculate the individual fitness of each candidate site, and hybrid optimization filtering operations such as selection, crossover, and variation are carried out according to the fitness to achieve the initial site selection planning objectives. The information and data of the initial planning site are updated, and continuously trained and iterated to screen out the site with the highest comprehensive fitness as the planning goal to complete site selection and optimization. The experimental results show that after applying the proposed method, the construction cost of the planned substation is controlled below 3 million yuan in each cycle, which is highly economical.

Key words: flood storage and detention area, substation, site selection optimization, GA-PSO, power supply coverage, power grid structure

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