Rapid evaluation method for power supply capability of urban distribution system based on N-1 contingency analysis of main-transformers

A proper evaluation on the power supply capability of urban distribution system is of much 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 (TIC) of transmission system, this paper proposes a straightforward method to evaluate the power supply capability (PSC) of distribution system, which is based on N - 1 contingency analysis of interconnected main-transformers. 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 loadability of each main-transformer is concluded through the N - 1 contingency analysis of every interconnected group. Finally, based on a comprehensive analysis of all the interconnected groups' results, the maximum permissible loadability of each main-transformer can be obtained, thus the PSC of the entire distribution system can be calculated. Through the application in a distribution system of Shanghai, China, the effectiveness and the accuracy of the method are demonstrated. The application results suggest that, the method presented in this paper is a simple and practical tool to evaluate the PSC of a distribution system, which needs only one calculation with constraints according to the N - 1 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. (C) 2010 Elsevier Ltd. All rights reserved.