Solving optimal reactive power problem by enhanced fruit fly optimization algorithm and status of material algorithm

Abstract

This paper proposes enhanced fruit fly optimization algorithm (EFF) and status of material algorithm (SMA) to solve the optimal reactive power problem. Fruit fly optimization algorithm is based on the food finding behavior of the fruit fly. There are two steps in food finding procedure of fruit fly: At first it smells the food source by means of osphresis organ and it flies in that direction; afterwards, when it gets closer to the food site, through its sensitive vision it will find the food. At the beginning of the run by diminishing the inertia weight from a large value to a small value, will lead to enhance the global search capability and more local search ability will be in process the end of the run of the EFF algorithm. Then SMA is projected to solve the problem. Three state of material are solid, liquid, and gas. For evolution procedure direction vector operator assign a direction to every molecule consecutively to guide the particle progression. Collision operator imitates the collisions factor in which molecules are interacting to each other. Proposed enhanced EFF, SMA has been tested in standard IEEE 30 bus test system and simulation results show the projected algorithms reduced the real power loss considerably.