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

• Main Authors: Yulan Shen, Yanbo Chen, Ji Zhang, Zixia Sang, Qiangming Zhou
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Self-healing; uncertainty; quantitative indicators; evaluation; smart distribution network
• Online Access: https://ieeexplore.ieee.org/document/8825776/

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.