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基于关联规则挖掘与组合赋权-云模型的电网二次设备运行状态风险评估

基于关联规则挖掘与组合赋权-云模型的电网二次设备运行状态风险评估

ISSN:1674-3415
2021年第49卷第10期
应用研究
南东亮,王维庆,张 陵,陈 凯,杨国生,张 路,孙永辉 NAN Dongliang, WANG Weiqing, ZHANG Ling, CHEN Kai, YANG Guosheng, ZHANG Lu, SUN Yonghui
(1.新疆大学电气工程学院,新疆 乌鲁木齐 830047;2.国网新疆电力有限公司电力科学研究院,新疆 乌鲁木齐 830011;3.河海大学能源与电气学院,江苏 南京 210098;4.中国电力科学研究院有限公司,北京 100192) (1. School of Electrical Engineering, Xinjiang University, Urumqi 830047, China; 2. Electric Power Research Institute of State Grid Xinjiang Electric Power Co., Ltd., Urumqi 830011, China; 3. College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China; 4. China Electric Power Research Institute Co., Ltd., Beijing 100192, China)

针对当前电网二次设备周期性检修效率低、评估结果过于依赖专家主观经验的问题,提出一种基于关联规则挖掘与组合赋权-云模型的二次设备运行状态风险评估方法.首先,基于Apriori关联规则挖掘算法筛选评估指标,构建二次设备运行状态风险评估指标体系.其次,采用属性层次分析法和反熵权法分别计算评估指标的主、客观权重,并基于合作博弈...

In view of the low efficiency of periodic maintenance of secondary equipment in the current power grid, and the evaluation results are too dependent on the subjective experience of experts, a risk assessment method for the operation status of secondary equipment based on association rule mining and combination weighting-cloud model is proposed. First, based on the Apriori association rule mining algorithm, the evaluation index is screened, and the risk evaluation index system for the operation status of the secondary equipment is constructed. Secondly, the attribute analytic hierarchy process and the anti-entropy method are used to calculate the subjective and objective weights of the evaluation indicators, and the combined weights are obtained based on the cooperative game model. Finally, a secondary equipment risk assessment model is built based on cloud model based on cloud theory. Example analysis shows that the method is simple and easy to implement, improves the scientificity and accuracy of the evaluation results, and assists the operation and maintenance personnel of the secondary equipment of the power grid to make scientific and reasonable maintenance decisions. This work is supported by the National Natural Science Foundation of China (No. 51667020).

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ISSN:1674-3415
2021年第49卷第10期
应用研究

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