Research On Reactive Power Optimization And Energy Saving And Loss Reduction Of Power Grid Based On Improved Genetic Algorithm

In this paper,the objective function of reactive power optimization is to reduce the active power loss of the system,and the penalty function is used to prevent the node voltage from exceeding the limit and the generator reactive power output from exceeding the limit while satisfying the power flow and variable constraints.Genetic algorithm is selected as the tool of reactive power optimization.In order to improve the performance of simple genetic algorithm,hybrid coding,single point crossover operation and nonlinear programming function fmincon are used.The improved genetic algorithm in this paper is used to simulate and verify in the field of mathematics and power system through MATLAB.In order to verify the function of finincon function in the improved genetic algorithm,the improved genetic algorithm is divided into two kinds of optimization algorithms:one is the improved genetic algorithm,the other is the removal of fmincon function,the other parameters and the improved scheme are the same as the improved genetic algorithm.Through the analysis of simulation results,it can be concluded that fmincon function plays a very important role in the optimization process of the improved genetic algorithm,and the improved genetic algorithm is superior to the simple genetic algorithm in both convergence speed method and convergence accuracy,which verifies the effectiveness of the improved genetic algorithm in this paper.