A Research On Distribution Network Planning With Distributed Generation

The location and capacity of distributed generation, which have great influenceon distribution network, are discussed in this paper. Based on the description ofcharacteristics, significance and current situation of distributed generation, theapplication of multiple DG technology are analyzed in detail. And the establishmentof the multiple target model and improved multi-objective particle swarmoptimization algorithm are deeply studied. The specific works are as follows:In the field of the distributed generation planning, the attention should be paidfor the environmental benefits of the DG. The model established in this paper meetthe system the constraints and maximize access system DG total capacity, to reducethe traditional grid power emission and bring the environmental benefits, the systemnetwork loss and the safe and stable operation of the system are also considered. TheDG multi-objective model is established to improve environmental efficiency,reduce the network loss and maximize static voltage stability margin.In the planning of distribution network, the location of the distributed powerwith the capacity problem is a multi-objective optimization problem, and the modelmay contain mutually restricted target function. This paper puts forward amulti-objective particle swarm algorithm, uses adaptive grid and roulette method tochoose the global optimal particle, and uses fuzzy global best position to promoteparticles in the search area outside the track so as to reduce the prematureconvergence and make the whole Pareto front search approximation. A externalstorage is set up to keep the Pareto optimal solution found in a search process, Theadaptive grid method is used for the renewal and the maintenance operation ofexternal memory optimal solution, make leadership particles lead the real particleswarm to find optimal Pareto solutions. This algorithm solves the global optimalparticle choice and diversity of evolution population loss, and has good convergenceand uniform distribution, it can also obtain several optimal solution for running onetime, and coordinate the relationship between the objective functions, and find outthe optimal solution set to meet the goals, the optimization select the optimalsolution according to the actual system personnel compare each target for power gridplanning. Finally the example results verify the feasibility and validity of the modeland algorithm.