BACK PROPAGATION NEURAL NETWORK TECHNIQUE FOR REDUCTION OF REAL POWER LOSS

In this work particle swarm optimization algorithm has been hybridized with Back propagation neural network (PSBP) to solve the reactive power problem. Proposed PSBP methodology improves search. PSO algorithm to optimize the original weight, threshold value and when the algorithm ends, optimal point can be found- on the base of PSO algorithm; Back propagation neural network algorithm to search overall situation and then achieve the network training goal. In the particle swarm, every particle's position represents weights set among the network during the resent iteration. In order to evaluate the proposed algorithm, it has been tested on IEEE 118 bus system and compared to other algorithms and simulation results show that proposed algorithm reduces the real power loss effectively.