Optimization of Optimal Power Flow considering Location of FACTS Devices using Partial Reinforcement Optimizer

Abstract

Optimal power flow (OPF) is the most addressed modern power system planning and operating optimization problem. The complexity of the OPF problem is quite high due to constraints. It becomes a very difficult and high complexity optimization problem with the inclusion of the optimal location and rating of flexible AC transmission system (FACTS) devices. Therefore, in order to obtain the optimal solution for the problem, it is necessary to use the most suitable meta-heuristic search (MHS) algorithm for the structure of OPF problem. In this paper, an up-to-date and strong MHS algorithm known as partial reinforcement optimizer (PRO) were used to solve the OPF problem considering optimal location and rating of the multi-types FACTS devices. The objectives considered in the study were minimization of total cost, minimization of total cost with valve-point loading effect, and minimization of the real power loss. In the simulation studies, four case studies were solved by PRO algorithm and its three rivals such as dingo optimization algorithm, evolutionary mating algorithm, and snow geese algorithm. According to the results of the case studies, PRO algorithm obtained the best solution among them. The performance of PRO algorithm were evaluated using Friedman and Wilcoxon tests. The Friedman test results show that PRO algorithm achieved the best rank first with 1.2333 score value among them. In summary, PRO algorithm achieved a superior performance in solving these case studies.