Application of dynamic comprehensive evaluation method in power system emergency management capability assessment
DOI：10.19783/j.cnki.pspc.181174
Key Words:power system emergency management capability assessment  dynamic evaluation  timing weighted average operator  timing weighted geometric mean operator  indicator system
Author NameAffiliationE-mail
WANG Di School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China  
CAI Dongjun* State Grid Ningbo Power Supply Company, Ningbo 315000, China 11317566@qq.com 
FANG Xinyan School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China  
FANG Zhongshan State Grid Ningbo Power Supply Company, Ningbo 315000, China  
HU Zhenqi State Grid Ningbo Power Supply Company, Ningbo 315000, China  
DING Pengkun School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China  
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Abstract:Most of the traditional grid emergency management capability assessment models use static evaluation. The conclusions drawn by this method are one-sided. In response to this deficiency, this paper proposes a dynamic evaluation method to make the evaluation results more reasonable and comprehensive. The basic index system of power grid emergency management capability assessment is established. The analytic hierarchy process and the coefficient of variation method are used to combine the objective and objective methods to assign weights to each index and perform static evaluation. The emergency management capability assessment is divided into four periods:prevention, preparation, response and recovery. The time-weighted average-time-series weighted geometric average hybrid operator model is used to analyze the grid emergency management capability to obtain the dynamic comprehensive evaluation value. The results show that the dynamic comprehensive evaluation method can be used to evaluate the emergency management capability of the power grid to obtain scientific and accurate results. This work is supported by National Key Research and Development Program of China (No. 2016YFC0205204).
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