Optimal Reactive Power Planning Of Radical Distribution System On Improved Genetic Algorithm

The reactive power optimization of a radial distribution system can efficiently minimize the real power losses and improve voltage level of it, so that the yearly running charge will be reduced and the quality of power energy can be increased. There are two directions to research in the reactive power optimization: One is that the mathematical model used in reactive power planning is in line with realistic situation; the other is that the solving methods are modified to deal with the problem of local optimum and computational burden.SGA has defects of slow convergence and being prone to immature convergence. In order to eliminate the defects, an improved GA is proposed in this paper. This paper introduces cataclysm for adjusting the population size through removing redundant similar chromosomes, constructs diverse fitness based different period in order to increase the convergence speed, uses alterable rate of cross and variation in order to reduce calculating time of GA.In order to enhance convergence velocity of reactive power optimization of the radial distribution system, combining the characteristic of the radial distribution system, a sensitivity analysis approach was build up for optimal selection of capacitors and mutation of transformer tap changer. Heuristic mutation capacitors basing on practice are proposed.In this paper, we present the objective function considering energy loss and investment of reactive compensation equipment at diverse load levels, Penalty function is considered to deal with variables violating the constraints. The mathematical model is established which takes all practical constraints and reactive power regulation measures into considered. The candidate locations for capacitor are situated in the end of 10kV line. A genetic algorithm with sensitivity analysis is designed to limit the number of candidate locations for capacitor. At the same time, unitary search ability of GA is improved, calculating time is reduced greatly and stability of GA is advanced.Based in the proposed mathematical model and algorithm, a computer program is developed. 28-node feeder and a radial distribution system are studied. All the results given in the paper shows that the improved genetic algorithm is stable and fast and is suitable for practical application medium-scale power system.