Self-Healing Evaluation of Smart Distribution Network Based on Uncertainty Theory

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Abstract

The existing self-healing evaluation of smart distribution network mainly has the problem of uncomprehensive quantitative indicators and neglecting the uncertainty in self-healing process, which leads to inaccurate evaluation higher than the actual result. In order to solve the above problems, this paper carries out two aspects of work: 1) four quantitative indicators, namely self-healing credibility, self-healing rate, self-healing speed, and self-healing benefits for smart distribution network are proposed firstly; based on the above four indicators, a comprehensive evaluation index of self-healing performance is then proposed by using entropy weight method; 2) uncertainty theory is used to quantitatively describe the uncertainty of self-healing, thereby solving the problems of uncertainty and insufficient samples in self-healing evaluation process. The effectiveness of the proposed method is verified by numerical simulation.

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Shen, Y., Chen, Y., Zhang, J., Sang, Z., & Zhou, Q. (2019). Self-Healing Evaluation of Smart Distribution Network Based on Uncertainty Theory. IEEE Access, 7, 140022–140029. https://doi.org/10.1109/ACCESS.2019.2939537

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