基于可拓云模型与模糊贴近度的电能质量评估研究

针对电能质量评估中存在主观性和不确定性，提出一种基于可拓云模型与模糊贴近度的电能质量评估方法。首先，计及电能质量等级分类处的模糊性和随机性，以可拓云理论为基础构建电能质量评估框架；其次，运用云熵优化兼顾2种不同云熵计算方法的特点确定新的云熵值，得到改进可拓云模型来计算每个指标对应质量等级关联度；最后，借鉴TOPSIS法确定电能质量指标正负理想等级，通过比较每个非对称贴近度向量与正负理想等级的贴近情况判定最终电能质量评估结果。某变电站10 kV母线实测数据验证了该方法的准确性和有效性。

Power Quality Evaluation Based on Extension Cloud Model and Fuzzy Proximity Degree

Targeting the problem of subjectivity and uncertainty in power quality evaluation，the paper proposes a power quality evaluation method based on extension cloud model and fuzzy proximity degree. Firstly， considering the fuzziness and randomness of power quality classification，the power quality evaluation framework is constructed based on extension cloud theory. Secondly，a new cloud entropy value is determined by combining the characteristics of two different cloud entropy calculation methods with cloud entropy optimization，and then an improved extension cloud model is obtained to calculate the correlation degree of the quality grade corresponding to each index. Finally，the asymmetric proximity degree vector of the feature subset corresponding to each index quality grade is obtained based on fuzzy proximity degree， TOPSIS method is used to determine an positive and negative ideal grade of the power quality index，and the final power quality assessment is completed by comparing the nearness between each asymmetric proximity degree vector and the positive and negative ideal grade. The accuracy and effectiveness of the proposed method is verified by taking the measured 10 kV bus data from a substation as an example.