Research Of Reactive Power Optimization Based On Improved Genetic Algorithm

Secure, economic and steady operation of power system affects all aspects of social life. To realize secure and economic operation of power system, the reasonable distribution of power system reactive power is an important measure. And it is an important method to improve the voltage quality, to make full use of reactive power, to reduce network losses, to enhance system stability. It is always the concern issue.In this thesis, research is based on home and abroad. It makes an in-depth study of the power system reactive power optimization features and development trend, and the requirements of the optimize algorithm. Mathematical model is established on power system active power loss minimum as the objective function, the node voltage violation and generator reactive power output crossing node as the penalty function. There are three methods of power flow calculation, Newton-Raphson, Gauss-Seidel, and the fast decoupled method. Three power flow calculation methods are compared through analyzing and simulating. Based on the results of analysis and comparison, and taking into the characteristics of repeatedly power flow calculation in genetic algorithm, the fast decoupled method is utilized in the power flow algorithm, which is convenient to be programmed and improves the convergence rate.Considering the deficiencies of simple genetic algorithm and combining the characteristics of reactive power optimization, the binary and real number mixed coding method, adaptive cross and mutation probability; the method combination of logical crossover and linear cross are used, the superiority protection strategy and catastrophe strategy are adopted.IEEE-14and IEEE-30are used as examples to simulation analysis. The results show that this improved crossover operation of genetic algorithm reactive power optimization overcomes simple genetic algorithm has been caught early shortcomings in the certain extent and improves the stability of the algorithm, the computational efficiency, the convergence speed and global searching ability. In addition, it reduces the active power loss effectively, and realized safety, reliability and economic operation.