Research Based On Improved Particle Swarm Optimization Algorithm For Power Transmission Network Expansion Planning

Transmission expansion planning is a planning for the main grid of transmission system. It’s based on the load of the power system and the development of the power supply. It requires voltage quality and supply reliability, and it should fully meet the needs of the development of the system. With the expanding of the grid scale, the number of variables of the transmission grid planning has gradually increased, and the constraints also become more complex. It is too difficult for traditional mathematical optimization method to solve.Now there is a new way to solve this problem. It benefits from the development of Modern heuristic algorithm. Compared with other artificial intelligence heuristic method, the Particle Swarm Optimization algorithm is more easier to understand. And it calculates fast. It is much suitable for solving transmission network expansion planning such a large-scale nonlinear integer optimization problems.This article summarizes several solutions to solve the problem of transmission network planning with some mathematical models. It emphatically introduces the basic theory and mathematical model of the particle swarm optimization. To avoid the deficiency of Standard Particle Swarm Optimization algorithm (SPSO), that is, easily converge to the local optimum, an improved renewal equation of the particles’ velocities is used. One is nonlinear inertia weight with dynamical adaption, the other is an average minimum added to the renewal equation of SPSO. The calculated results of mathematical examples demonstrate that the improved PSO (MPSO) has better searching efficiency and faster converging speed than SPSO.The mathematical model of transmission network planning used in this paper, the objective function is sum value of the investment and loss-cost, the constraints are that the flow is reasonable and there are no overload lines in the network. IEEE Garver-6node system is computed are planned under normal condition separately by SPSO and MPSO. The results demonstrate that MPSO can get better planning scheme.