Application Of Genetic Algorithm In Oilfield Distribution Network Reactive Optimization

In this paper, the fundamental principles are introduced, which describe the genetic algorithm and the reactive power optimization of distribution network. The features and predominance of genetic algorithm to resolve the reactive power optimization problem are to be analyzed. Based on the features of oilfield distribution network, two optimization mathematics models are established, which aim to study the reactive power optimization problems of the oilfield distribution network. The two improved genetic algorithms are used to solve these two models. The preferable results are required .The results have an active role on the study and development of reactive power optimization of oilfield distribution network.The power flow calculation is studied. An exact mathematics model, which is an incidence matrix of nodes and lines matching the actual distribution network, is established. On the basis of the fundamental formula of power flow calculation, the computational process is improved. An iteration method is used to calculate the power flow.Several reactive power compensation fashions of distribution network are compared. In order to reduce the network loss and increase the power factor, furthest, the dispersion compensatory fashion is to be selected, that is to install power capacitor at the side of the distribution transformer, to make the network run better.The problem of optimal older to installing reactive power compensator is studied. The reactive power optimization mathematics mode is build based on the minimum the active power loss, out of limit of voltage and limit of investment scale as penalty function. The improved genetic algorithm with binary encoding,strategy of saving the classic chromosome,random sample select,adaptive probabilities of crossover and mutation and ameliorated stop criterion is used to resolve the mode. The improved algorithms converge more quickly than the traditional genetic algorithm.The problem of optimal capacity of reactive power compensator is studied. We establish an optimization mathematics mode with maximize income as objective function. The improved genetic algorithm with decimal encoding,initialization optimized,discrete recombine function and adaptive probabilities is used to resolve the mode. The better result is required.