Research on Improved Bat Algorithm for Multi-objective Optimal Power Flow Problem

To handle multi-objective optimal power flow (MOO PF) pro blem while satisfying various system constraints, a new multi-objective improved bat algorithm (MOIBA) is proposed. MOIBA algorithm can improve the shortcoming of basic bat algorithm which has weak global exploration and unsatisfactory diversity. To validate the performance of MOmA algorithm, IEEE30 bus system is implemented on MATLAB software to optimize, respectively, power loss and fuel cost concurrently, emission and fuel cost concurrently, power loss and emission concurrently. A Pareto-dominant Method with constraint (PDM) is employed to satisfy inequa Ii ty constraints of state variables. The results obtained by MOIBA algorithm, compared with MOPSO algorithm, show the effectiveness and superiority of proposed MOrnA algorithm in solving MOOPF problem.