Calculation of Line Losses in Distribution Systems Using Artificial Neural Network Aided by Immune Genetic Algorithm

In this paper,a method for calculating the line losses in distribution systems is presented using artificial neural network(ANN) aided by immune genetic algorithm(IGA),so as to overcome the shortcomings that back propagation neural networks(BPNN) is easily converged at a local minimum and the training process is slow.The mechanisms of diversity maintaining and antibody density regulation in a biological immune system are introduced into IGA based on genetic algorithm(GA).The proposed algorithm overcomes the problems of GA such as low search efficiency,bad individual diversity and premature enlarges the search space of weight and improves the training efficiency and precision of neural networks.Simulation results show that the BP neural networks designed by IGA have better performance in convergent speed and global convergence compared with hybrid genetic algorithm and that the method is more accurate than other ones.