Abstract

A proper evaluation on the power supply capability of urban distribution system is of enormous social and economical significance. In competitive marketing environment, to satisfy the sustainable growth of distribution loads, electric utilities must judge whether the return of power supply capability is sustainable and valued against the certain amount of investment. Therefore, to make up the insufficiency of traditional methods referring from the concept of total transfer capability of transmission system, this paper proposes a straightforward method to evaluate the power supply capability of distribution system, which is based on ldquoN-1rdquo simulation analysis of interconnected main-transformers under the ldquoN-1rdquo guideline. Firstly, a series of interconnected main-transformer groups are drawn from the main-transformers' interconnection analysis after the topological simplification of distribution system. Secondly, the maximum average load rates of main-transformers are concluded through the ldquoN-1rdquo simulation analysis of every interconnected group. Finally, based on a comprehensive analysis of all the interconnected groups' results, the maximum permissible load rate of each main-transformer can be obtained, thus the power supply capability of the entire distribution system can be calculated. Through the application in a district of Shanghai, China, the effectiveness and the accuracy of the method are demonstrated. The application results suggest that, the method presented in this paper based on ldquoN-1rdquo simulation analysis of interconnected main-transformers is a simple and practical tool, to evaluate the power supply capability of a distribution system, which will need only once calculation with constraint to the ldquoN-1rdquo guideline. Moreover, the interconnection weak-points and the interconnection bottlenecks of the distribution system can be identified easily with this approach, thus providing effective references for urban distribution network planning and the following project investment decisions.

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