Research on rural power grid planning method based on improved genetic annealing algorithm

Abstract

Current power grid planning mainly relies on planning experience in personnel selection schemes. Planning results of subjectivity are stronger, making the planning after the network loss difficult to meet the requirements. According to the above defects, research on rural power grid planning methods based on an improved genetic annealing algorithm is proposed. Using the directed graph, the operation mode of the rural power grid is analyzed, and the network load of different distributed power sources is calculated. The multi-objective programming model is established from two aspects of the economy and environmental protection of the rural power grid. The annealing algorithm is introduced in the crossover and mutation stage of the genetic algorithm. In the example experiment, the cost reduction of the improved genetic annealing algorithm is 57.45%, and the network loss rate is lower than that of the other planning methods, which makes the network power supply more reliable.