采用动态劣化度的风电机组运行状态实时评估  

Real-Time Wind Turbine Operating Assessment Using Dynamic Inferior Degree

作　　者：江顺辉 方瑞明[1] 尚荣艳[1] 王黎[1] 

机构地区：[1]华侨大学信息科学与工程学院,福建厦门361021

出　　处：《华侨大学学报（自然科学版）》2018年第1期86-91,共6页Journal of Huaqiao University(Natural Science)

基　　金：国家自然科学基金资助项目(51177039);福建省自然科学基金资助项目(2012J01223);福建省厦门市重大科技创新平台项目(3502Z20111008)

摘　　要：为满足大数据环境下风电机组状态评估的实时性要求,提出一种基于动态劣化度的实时状态评估方法.首先,建立动态劣化度计算模型;然后,引入正态云模型取代传统隶属函数,将正态云模型与模糊综合评价法相结合,形成风电机组运行状态实时评估方法;最后,基于辽宁某风电机组的SCADA数据,利用所述方法对其进行状态评估.实验结果表明:该方法能够准确把握机组的实时运行状态,并对其早期缺陷及时预警,有助于防范机组严重故障的发生.To meet the real-time requirements of a wind turbine conditions assessment under large data environment,based on dynamic inferior degree,this paper presents a novel real-time conditions assessment method.Firstly,the dynamic inferior degree calculation model is established.Then,introducing the normal cloud model to replace the traditional membership function.Furthermore,applying the normal cloud model into fuzzy synthetic evaluation method,a real-time operating conditions assessment method is given.Finally,the method is tested on the SCADA data of a wind turbine in Liaoning province.The results show that this method is capable of not only accurately assessing the real-time operating conditions of wind turbine,but also alarming its early defects timely,which is useful for wind turbine to prevent the occurrence of serious faults.

关 键 词：风电机组 动态劣化度 实时状态评估 马尔科夫链模型 正态云模型 

分 类 号：TM715[电气工程—电力系统及自动化]