Reactive Power Compensation Relate to Reactance Based on Modified Cataclysmic Genetic Algorithm

This paper presents an improved algorithm for reactive power compensation. The objectives is to minimized the power loss and the compensation cost and the percentage of overvoltage. Operation variables include the generator’s active power and reactive power output, the transformer tap, capacitor’s and reactance’s units. This research attempts to solve a complicated nonlinear mixed planning problem with multi-objectives. The traditional genetic algorithm (GA) is a global optimization method, but it has deficiency of long computation time and easily converging into local extreme value point. Modified cataclysmic genetic Algorithm (MCGA) can speed up the solution procedure and to make the solution near to the global optimum. Test results have been presented along with the discussion of the algorithm.