The Study Of Reactive Power Optimization Based On Improved Particle Swarm Optimization Algorithm

Reactive power optimization is one of the most important control methods to ensure power system operation securely and economically, and an effective measure to improve the voltage profile and reduce the transmission loss. Study the problem of reactive power optimization has the great significance in theory and practical application. Reactive power optimization is a large-scale nonlinear optimization problem with a large number of variables and uncertain parameters, the operating variables include continuous and discrete variables, so the optimization becomes very complex.This thesis established a mathematical model for reactive power optimization in power systems. The mathematical model had considered practical reactive power regulation facilities and operational constraints, and thus reflects the actual requirements of power systems. Then, made a deep research on reactive power optimization based on particle swarm optimization and tried to solve this problem with particle swarm optimization algorithm. A New search strategy is presented which called group-changeable inertia weight method. In addition, some other measure is also adopted to dispose restrictions, discrete variables and inactive particle.This thesis had made much improvement on the basic PSO. To accelerate the convergence speed and improve the search efficiency, a method of group-changeable inertia weight is adopted and a parameter of group-changeable inertia weight vector is also introduced. After every iterative computation, all of the particles are divided, into certain groups and each group is endued with different inertia from inertia...