LEI Chuanli, LUO Huiping, TANG Waiwen, et al. GA-PSO Hybrid Optimization Method for Substation Site Selection Under Constraint of Flood Storage and Detention Areas[J]. 2025, 45(4): 32-38.
LEI Chuanli, LUO Huiping, TANG Waiwen, et al. GA-PSO Hybrid Optimization Method for Substation Site Selection Under Constraint of Flood Storage and Detention Areas[J]. 2025, 45(4): 32-38. DOI: 10.3969/j.issn.1008-0198.2025.04.006.
GA-PSO Hybrid Optimization Method for Substation Site Selection Under Constraint of Flood Storage and Detention Areas
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