A Hybrid Reactive Power Optimization Algorithm Based on Improved Genetic Algorithm and Primal-dual Interior Point Algorithm

Based on improved genetic algorithm (IGA) and primal-dual interior point (PDIP) algorithm,a hybrid reactive power optimization algorithm is proposed. In this algorithm,at first the reactive power optimization problem is converted to integer nonlinear programming problem with discrete control variables which are solved by IGA; then by use of PDIP algorithm,the continuous variables which can match with the obtained most are solved,and the reactive power optimization is changed into a nonlinear programming problem with continuous control variables. In IGA,using crossover operator and mutation operator and based on the rule of feasible region the discrete constraints are processed,thus the global optimization efficiency of the hybrid optimization algorithm is raised. Numerical simulation results on the IEEE 118 test system show that the proposed method is effective. The proposed method has been applied in AGC system of Fujian power grid.