Solving OPF Problem Considering Environmental Concerns Using Self-Learning JAYA Algorithm

Abstract

Over the recent decades, the optimal power flow (OPF) problem has been favored by many scholars. In this paper, a multi-objective self-learning JAYA algorithm (MOSLJAYA) is put forward to handle the problem. Firstly, a new position updated equation containing the self-learning factor is used to coordinate the global search and local search capabilities of the population. Secondly, a modified crowding distance calculation method is introduced to maintain the uniform distribution of Pareto optimal solutions. To verify the effectiveness and robustness of MOSLJAYA, it was applied on two test systems with IEEE 30-bus and IEEE 57-bus test systems. Different experiments are designed to compare the extreme solutions, compromise solution of MOSLJAYA with several classic multi-objective algorithms. The results show that MOSLJAYA has good convergence and diversity, which can provide a powerful candidate to deal with OPF problems.