REAL POWER LOSS REDUCTION BY ENRICHED BLACK FISH OPTIMIZATION ALGORITHM - Kanagasabai, Lenin (IAES International Journal of Robotics and Automation (IJRA), 2020)
In this paper Enriched Black Fish Algorithm (EBA) has been utilized to solve the optimal reactive power problem. Bubble net hunting tactic has been imitated to form the Black Fish Algorithm (BA). Modernized solution is mainly depended on the current best candidate solution in Black fish optimization algorithm (BA). An inertia weight ? ? [1, 0] is introduced into Black fish optimization algorithm alike in particle swarm optimization algorithm, to acquire the Enriched black fish optimization algorithm (EBA). Roulette wheel selection method has been used to perk up the convergence rate of proposed enriched black fish optimization algorithm (EBA). The proposed EBA has been tested in standard IEEE 57,118 bus 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 limit