Multi-objective optimization method for location and capacity of a distribution network with distributed photovoltaic energy based on an improved FPA algorithm

In recent years, with the increasing amount of distributed PV in distribution network, unreasonable distributed photovoltaic access location and capacity has a large negative impact on the distribution network. Given this impact, a location and capacity model with the optimization objectives of minimum investment cost, minimum network loss and optimal voltage quality is proposed. The optimization model is solved by combining a genetic algorithm, a chaotic sequence and flower pollination algorithm. The pollen position is initialized by chaotic sequence to ensure population diversity. When the flower pollination algorithm is locally optimal, the optimal solution is used as the initial parameter of the genetic algorithm to select, cross and mutate to update the population, maintain the diversity of the population and improve the optimization ability of the algorithm. The feasibility of this method is verified by simulation. The results show that the convergence of the improved algorithm is significantly improved, from 300 iterations before the improvement to 40 iterations after the improvement. After the optimal configuration, the nodes and losses with poor voltage effect are significantly improved. This study provides a reference for the location and capacity of a distribution network with distributed generation. © 2022 Power System Protection and Control Press.