A Solution to the Load Flow Problem with Induction Motor using Modified Genetic Algorithm

摘要

This paper presents a solution to the load flow problem with induction motor using Modified Genetic Algorithm (MGA). The classical constant power load model is usually employed for load flow analysis. Since, the actual loads of power systems mostly have nonlinear voltage characteristics. The nonlinear load model is included into load flow problem that is essential to get better and precise results of load flow analysis. In this paper, the nonlinear model of induction motor load is included into the conventional load flow problem. Modified genetic algorithm involves a set of improved operators like Elitism, tournament selection and two point crossover, in order to increase its convergence speed and improve the quality of solution. In MGA, the objective function is to minimize the voltage and power mismatches and also constraining the power loss to a minimum value. This will results a precise solution to the load flow problem. To establish the validly of this method, the algorithm is tested with standard Ward-Hale six-bus system and with nine-bus system and the results are compared with simple genetic algorithm. It shows that speed of convergence is high and finds the precise solution for the problem.