Multi-objective Optimal Power Flow Using Improved Multi-objective Multi-verse Algorithm

Abstract

This study proposes an improved multi-objective multi-verse optimization (IMOMVO) algorithm for solving multi-objective optimal power flow (MOOPF) problem with uncertain renewable energy sources (RESs). Cross and self-pollination steps of flower pollination algorithm (FPA) along with crowding distance and non-dominating sorting approach is incorporated with the basic MOMVO algorithm to further enhance the exploration, exploitation and for well-distributed Pareto-optimal solution. To confirm the effectiveness of the proposed IMOMVO algorithm, modified IEEE 30-bus system with security constraints is utilized by considering the total generation cost and active power loss minimization. The simulation results obtained with IMOMVO is compared with MOMVO, NSGA-II, and MOPSO, which reveals the capability of the proposed IMOMVO in terms of solution optimality and distribution.