基于最优权重和隶属云的风电机组状态模糊综合评估  

Fuzzy Comprehensive Assessment of Wind Turbines Status Based on Optimal Weight and Membership Cloud

作　　者：赵洪山[1] 张健平[2] 李浪[1] 

机构地区：[1]华北电力大学电气与电子工程学院,河北保定071003 [2]国网沧州供电公司,河北沧州061000

出　　处：《中国电力》2017年第5期88-94,共7页Electric Power

基　　金：国家科技支撑计划资助项目(2015BAA06B03)~~

摘　　要：针对风电机组状态模糊综合评估存在评估指标权重和隶属度确定主观性强的问题,提出了一种基于最优权重和隶属云的风电机组状态模糊综合评估方法。首先,采用层次分析法(AHP)构建状态评估指标体系,引入相对劣化度对状态评估指标进行归一化处理和状态等级划分;其次,采用熵权法和AHP分别确定状态评估指标的客观和主观权重,并通过非线性规划最优化解法确定状态评估指标的最优权重;然后,利用正态隶属云的概念及生成算法,确定状态评估指标对各状态等级的隶属度,构成评估矩阵;最后,通过实例仿真,并与其他评估方法进行比较,验证该方法是更加有效的和合理的。In order to overcome strong subjectivity of empowerment and membership evaluation of status assessment indices in fuzzy comprehensive assessment （FCA）, a FCA wind turbine status assessment algorithm is proposed based on optimal weight and membership cloud. Firstly, status assessment indices system is established based on analytic hierarchy process （AHP）. The relative deterioration degree is introduced to normalize assessment indices and divide condition levels. Then, entropy weight method and AHP are used to determine objective and subjective weights respectively to obtain optimal integrated weight by nonlinear programming. Next, by utilizing generation algorithm of normal membership cloud, the memberships of assessment indices are obtained to build evaluation matrix. Finally, comparing of simulation results with other assessment methods validates effectiveness of proposed method.

关 键 词：风电机组 状态评估 最优权重 隶属云 模糊综合评估 

分 类 号：TM614[电气工程—电力系统及自动化]