Optimal placement and sizing of photovoltaic power plants in power grid considering multi-objective optimization using evolutionary algorithms

Abstract

During the past decade, the effect of renewable and non-renewable Distributed Generation (DG) sources of production has grown all over the world. Also, it has enhanced by national and international policies aimed at increasing the share of renewable energy sources and combining small high efficient heat and power plants to reduce greenhouse gas emissions, and global warming have been encouraged. Although the installation and operation of DGs have discussed for solving network problems in distribution networks, the fact is that in most cases, Distribution System Operator has no control or influence over DG placement and size. In this article, a meta-heuristic algorithm for management and decision-making for optimal selection is presented, and in choosing the optimal solution, the impact factor is suggested in the best case. Inappropriate DG placement may increase system losses, network investment, and operating costs. This paper determined the optimal capacity and placement of photovoltaic sources to reduce losses, improve the voltage profile, and increase the active power to reactive power lines in MATLAB software by the second version of the genetically engineered algorithm with unstable Non-dominated Sorting Genetic Algorithm (NSGA-II).