Real-time assessment of operational risk of coal-fired power generation based on big data

被引：0
|
作者：
Li C. [1 ]
Dong J. [1 ]
Ding J. [1 ]
机构：
[1] School of Economics and Management, North China Electric Power University, Beijing
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2022年 / 50卷 / 16期
基金：
中国国家自然科学基金;
关键词：
big data; coal-fired power generation; evidence theory; grey relational analysis; risk assessment;
D O I：
10.19783/j.cnki.pspc.211415
中图分类号：
学科分类号：
摘要：
Coal-fired power generation units are faced with various risks in their operation. A fault can cause considerable economic loss and social impact. In order to ensure the safe production and stable operation of the unit, a real-time assessment model of operational risk of a coal-fired power generation is established, so as to formulate the troubleshooting plan in time. Based on big data association rules, the association relationship between the operation risk of coal-fired power generation and impact factors is analyzed. The impact factors are weighted based on the entropy weight method, and the determination and fusion of the basic reliability distribution function are realized by combining the grey correlation theory, evidence theory and Dempster synthesis rules, so as to obtain the operation risk value and risk level of a coal-fired power generation unit. Finally, taking the coal-fired power generation unit of power plant A as an example, the risk assessment results are consistent with the actual operation. This proves the practical significance of the model. © 2022 Power System Protection and Control Press. All rights reserved.
引用
收藏
页码：47 / 57
页数：10
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