REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM

Abstract

This paper presents a Mutual Mammal Behavior (MM) algorithm for solving Reactive power problem in power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization is taken is taken as main objective. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. A Meta heuristic algorithm for global optimization called the Mutual Mammal Behavior (MM) is introduced. Mammal groups like Carnivores, African lion, Cheetah, Dingo Fennec Fox, Moose, Polar Bear, Sea Otter, Blue Whale, Bottlenose Dolphin exhibit a variety of behaviors including swarming about a food source, milling around a central location, or migrating over large distances in aligned groups. These Mutual behaviors are often advantageous to groups, allowing them to increase their harvesting efficiency, to follow better migration routes, to improve their aerodynamic, and to avoid predation. In the proposed algorithm, the searcher agents emulate a group of Mammals which interact with each other based on the biological laws of Mutual motion. MM powerful stochastic optimization technique has been utilized to solve the reactive power optimization problem. In order to evaluate up the performance of the proposed algorithm, it has been tested on Standard IEEE 57,118 bus systems. Proposed MM algorithm out performs other reported standard algorithm’s in reducing real power loss.