Reactive Power Compensation Of Distribution Network Based On Particle Swarm And Immune Optimization Algorithm

The reactive power compensation optimization always occupies the importantpart in power system planning and operation in safety and economy.And with theincreasing distribution generations involving in distribution network become moreand more, it will bring a new meaning to the solving reactive power compensationoptimization.Firstly,the power system example has been processed into mathematical model inwhich each kind of distribution generation has its own model and the topology ofnetwork has been built, as to the objective function on this optimization, the costabout the system power loss and reactive compensation equipments is involved;secondly, the forward and backward sweep method with reactive injectingcompensation principle is proposed, correspondingly the constraints include nodes’voltages level is in qualified range, power is limited by certain values and in balance;thirdly, the mixed artificial intelligence algorithms combined with binary particleswarm optimization algorithm and artificial immune algorithm is proposed and builtby MATLAB, which lead to high algorithm’s global search ability benefited fromartificial immune algorithm and fast convergence rate from particle swarm algorithm;finally, since the reality of distribution generation power and users load change withdifferent climates, the system operation model will be divided into four differentstyles by four seasons and it will lead a more realistic output.The example of this article includes a28-node system and a33-node system.Through these two examples’ calculation, the results proved that the algorithmproposed in this article can solve the reactive compensation optimization problem ona distribution generation involved in system effectively.The optimization data isimpressive,which can show this kind of algorithm is practical and useful.