Planning Of Distributed Generation In Distribution Network Based On Genetic Algorithm

With the development of the power technology, the daily increasing load demand and the expansion of the generation size, problems of the big electric network gradually emerge, such as the hard tracking of power system to the load's change, low system reliability, large line loss of transmission system and distribution system, serious environment pollution, so it has been unable to meet the quality and security requirements of electric power supply. Distributed generation (DG) has many advantages, such as reducing the pollution to environment and lowing charge to users, improving quality of the electric energy and security of the power supply, easy tracking of power system to the load's change, be able to meet the requirements of sustainable energy development, so supplement and corresponding with the big electric network, distributed generation is the best way to supply the reliable and high-quality electric power to users by making good use of existed resource and equipment.Most users would like to use electric power supplied by both DG and the big electric network, except some remote or special areas which must use DG only. So we must consider that how DG to operate with the big electric network, when more and more DG have appeared in distribution network planning project and the systemic complexity has been increased consumedly by introducing a mass of random changes. Because the traditional planning methods have simplified the planning problem more or less and lack good treatment for the uncertainties which is existent impersonality but hard to express, it is unable to solve the problem of distribution network planning including DG.The paper makes some analysis and research about the distribution network planning including DG. Firstly, the paper introduces conception and class of DG and its development situation at home and abroad, also introduces several technologies of DG and its advantages. Secondly, for a single planning of distribution network including DG, based on considering economy and security of distributed generation, constructing a multi-objective optimal model, which including the minimum investment cost of distributed generation and the minimum power loss of distribution network and the maximum static voltage stability margin. The paper introduces total satisfied degree by employing the fuzzy optimal theory, which makes a good way to transform multi-objective into single objective, in order to get the best project in all. Lastly, the genetic algorithm has some disadvantages when resolving the planning model such as slow convergence and easy to precocity. In order to overcome the shortcomings of genetic algorithm, a new improved self-adaptive genetic algorithm was proposed in this paper. The paper use a system simulation results to verify the proposed model correction, prove the improved self-adaptive genetic algorithm is more effectively in seeking the best result of overall situation and increasing the convergence speed than genetic algorithm.