Abstract
The safety and reliability of urban power supply are critical to the sustainability of cities and society. Based on the analysis of big data, a power supply reliability evaluation method for urban distribution networks considering uncertain factors is proposed in this paper. The method has good adaptability and can support the analysis of safety improvement measures. By investigating historical data on distribution network topology and parameters, the main influencing factors affecting power supply reliability and the uncertainties of these factors are screened out. An improved Elman neural network (IENN) is used, and the main process of reliability evaluation is obtained for the complex urban distribution network. It can effectively simplify the calculation and includes multiple uncertain factors to improve evaluation accuracy. Case studies with actual urban distribution network data are used to verify the feasibility and effectiveness of the proposed method. Finally, some useful conclusions are given, including the problems of urban distribution network power supply, and the improvement measures for power supply to support the development of sustainable cities and society.
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