Reactive power optimization research of power system considered the generation transmission and distribution

The measure of reactive power optimization of main power network mainly considers on-load tap changer, the optimal capacity of the capacitor, the voltage of generator under the steady load. Reducing active power loss is considered of the main object function. The model of reactive optimization is established based on these. And the penalty function is considered to deal with variables violating the constraints. Genetic algorithm is applied in solution of reactive power optimization. It belongs to complex nonlinear optimization problems. This paper made some improvements using real coding and dynamic crossover and mutation rate. Improved algorithm can avoid converging to a local optimal solution, and the speed and precision are boosted to a certain extent. Based on the proposed mathematical model and algorithm, The program is made by C++ language. The algorithm is applied to the IEEE 14 bus system. The results of the study clearly indicate that the proposed method is very useful to reactive power optimization.