Abstract

This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in power system. The basic Particle Swarm Optimization (PSO) algorithm and its principle have been introduced, the Particle Swarm Optimization has low accelerate speed and can be easy to fall into local extreme value, so the Particle Swarm Optimization based on the improved inertia weight is presented. This method means using nonlinear decreasing weight factor to change the fundamental ways of PSO. To allow full play to the approximation capability of the function of BP neural network and overcome the main shortcomings of its liability to fall into local extreme value and the study proposed a concept of applying improved PSO algorithm and BP network jointly to optimize the original weight and threshold value of network and incorporating the improved PSO algorithm into BP network to establish a improved PSO-BP network system. This method (BP-IPSO) improves convergence speed and the ability to search optimal value. We apply the improved particle swarm algorithm to reliability prediction. Compared with the traditional BP method, this kind of algorithm can minimize errors and improve convergence speed at the same time. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms and simulation results show that (BP-IPSO)   is more efficient than others for solution of single-objective ORPD problem.

Key words: BP improvement, neural network, reliability prediction, the improved PSO, optimal reactive power, Transmission loss.