| With the development of the power technology and the daily increasing load demand, the size of the power system is increasingly expanding. The big electric network has difficulty in tracking the load changes flexibly, energy consumption and environment pollution are more serious, all these problems make the distributed generation(DG) techology more and more popular in our country. DG possesses many advantages, such as flexibility, saving investment and compatiblity. So corresponding to the big electric network, DG is the best way to supply the reliable and high-quality electric power to users by making good use of existing resource and equipments.When more and more DGs appeare in distribution network, the systemic complexity has been increased greatly by introducing a mass of random. We must consider how to operate DG with the big electric network, DG has a great impact on power flow, node voltage, short circuit and reliability of distribution network and the degree of impact is closely related to the size and site of DG Therefore, suitable location and optimal sizing are crucially important to the planning of distribution systems.In this thesis, on the basis of summarizing the single-objective distribution network planning model and considering the two aspects of security and economy, a multi-objective optimal scheme is proposed, which includes the maximum static voltage stability margin and minimum power loss of distribution network and the minimum investment cost of distrbuted generation. Secondly, the thesis introduces total satisfied degree by employing the fuzzy theory, which makes a good way to transform multi-objective into single objective. Lastly, a new improved self-adaptive genetic algorithm is employed to solve the planning modle. The case studies have been carried out on distribution test system and simulation resuls, which shows that the proposed algorithm can increase the convergence speed and favorable self-adaptive characteristics than genetic algorithm. |
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