Decline of Active Power Loss by Improved Moth-Flame Optimization Algorithm

In this paper, Improved Moth-Flame Optimization (IMFO) algorithm has been proposed for solving Reactive power problem. Navigation method of moths in nature called transverse orientation is the key inspiration of the moth-flame algorithm (MFO). By maintaining a fixed angle with respect to the moon, Moths fly in the night and it’s an effective mechanism for moths travelling in a straight line for long distances. Due to very slow convergence and poor precision, an improved version of MFO algorithm based on Levy-flight strategy has been proposed to solve the reactive power problem. The diversity of the population can be increased by Levy-flight to overcome premature convergence in order to reach the global optimal solution. This methodology improves the trade-off between exploration and exploitation ability of moth-flame algorithm (MFO).The proposed Improved Moth-Flame Optimization (IMFO) algorithm has been tested in standard IEEE 30,57,118 bus test systems and simulation results show clearly about the better performance of the proposed algorithm in reducing the real power loss with control variables within the limits