Hunan Electric Power ›› 2025, Vol. 45 ›› Issue (4): 32-38.doi: 10.3969/j.issn.1008-0198.2025.04.006

• Expert Column:Electric Power Prevention and Reduction • Previous Articles     Next Articles

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

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

CLC Number: