基于逆向云的电能质量扰动综合评估方法

充分考虑扰动分类等级边界值具有的随机性和模糊性,结合云模型的不确定推理特性与物元分析理论的优点,提出了一种基于逆向云发生器的电能质量扰动综合评估模型。通过逆向云发生器建立电能质量扰动综合评估的标准模型,在此基础上通过实时的数据分析,对现有模型进行实时修正,使得扰动综合评估模型具有更强的实时性。针对电能质量扰动综合评估的特点,将层次分析法、灰色聚类评估法相结合得到扰动综合评估中各项指标的权重值使得扰动综合评估结果可信度更高。对金属厂的中频炉和牵引变电站的试验分析验证了该模型的优越性和有效性。

A Disturbance Evaluation Model of Power Quality Based on Backward Cloud Theory

The boundary value of disturbance classification levels is fuzzy and random. And the cloud model is an uncertain transformation model describing the qualitative concept and quantitative processing. By fully considering these characteristics and combining the advantages of cloud model such as uncertainty reasoning characteristics and matter element analysis theory, a synthetic disturbance evaluation model is proposed based on the theory of backward cloud matter element. The standard model is established with backward cloud generator for synthetic disturbance evaluation of power quality, and the model is constantly updated through real-time data analysis, which makes the disturbance evaluation model more realtime. According to the characteristics of the disturbance evaluation of power quality, the weights of all the indices in power quality synthetic evaluation are obtained by integrating three methods, including the analytic hierarchy process method, the grey cluster method and the entropy method, which makes the disturbance evaluation result more credible. The superiority and effectiveness of the model are demonstrated by using the results of the actual numerical tests in the IF furnace of metal factory and the traction substations.