Abstract
As the distribution network environment becomes more complex, improving the optimization effect and running time is the key to distribution network reconfiguration. In this paper, firstly, the minimum branch power loss is used as the evaluation index of the result, and the hybrid algorithm of PSO algorithm and CS algorithm is selected as the optimization method of the reconstruction problem. Secondly, the mathematical model of the distribution network introduced by DG is simplified, and the static distribution network weight is used. It is a simplified way of power flow solving by introducing DG into the distribution network model. Based on the CS-PSO algorithm, the optimization calculation of the distribution network reconfiguration with DG is carried out. Finally, a calculation example proves the rationality and effectiveness of the method.
Highlights
Power system is an important infrastructure of modern society, and its safe and reliable operation is an important guarantee for people's normal social and economic life [1,2]
Draw the charging load curve through the charging model, divide the time segment according to the characteristics of the curve, make reconstruction optimization in each time period with its own characteristics, consider the three factors of network loss, voltage quality, and balanced load, and use particle swarm optimization algorithm to simplify the calculation of the mathematical model of EV introduction into the distribution network
Due to the high stability of the PSO algorithm, the PSO algorithm is the main body of the CS-PSO algorithm, and the CS algorithm is supplemented
Summary
Power system is an important infrastructure of modern society, and its safe and reliable operation is an important guarantee for people's normal social and economic life [1,2]. With one day as the calculation period, considering the random output of DG and the timing change of EV charging and discharging, the minimum network loss is taken as the objective function, and the improved genetic algorithm is adopted as the optimization method. Draw the charging load curve through the charging model, divide the time segment according to the characteristics of the curve, make reconstruction optimization in each time period with its own characteristics, consider the three factors of network loss, voltage quality, and balanced load, and use particle swarm optimization algorithm to simplify the calculation of the mathematical model of EV introduction into the distribution network. Literature [7] uses the power flow characteristics after the reconfiguration of the distribution network to optimize the large DG access location and its output, uses random power flow and Monte Carlo to simulate uncontrollable DG, and combines DG to achieve power flow optimization and reduce lines power consumption and improve reliability
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