基于改进劣化度模型的风电机组日常运行状态评估  

EVALUATION OF WIND TURBINES DAILY OPERATION CONDITIONS BASED ON IMPROVED DEGRADATION MODEL

作　　者：金晓航 秦治伟 郭远晶[4] 单继宏 Jin Xiaohang;Qin Zhiwei;Guo Yuanjing;Shan Jihong(College of Mechanical Engineering,Zhejiang University of Technology,Hangzhou 310023,China;Key Laboratory of Special Purpose Equipment and Advanced Processing Technology,Ministry of Education and Zhejiang Province,Zhejiang University of Technology,Hangzhou 310023,China;Ninghai ZJUT Academy of Science and Technology,Ninghai 315600,China;Zhijiang College,Zhejiang University of Technology,Shaoxing 312030,China)

机构地区：[1]浙江工业大学机械工程学院,杭州310023 [2]特种装备制造与先进加工技术教育部/浙江省重点实验室(浙江工业大学),杭州310023 [3]宁海县浙工大科学技术研究院,宁海315600 [4]浙江工业大学之江学院,绍兴312030

出　　处：《太阳能学报》2023年第1期239-246,共8页Acta Energiae Solaris Sinica

基　　金：国家重点研发计划(2022YFE0198900);宁波市自然科学基金(2021J038)。

摘　　要：为准确地掌握整台风电机组的运行状态,提出一种基于改进劣化度模型的评估方法。首先求得风电机组层次结构中各状态参数的劣化度;其次通过组合赋权法确定各参数的权重,利用岭型分布隶属度函数确定各参数的隶属度矩阵;最后利用模糊综合评判法和彩色图谱对机组的运行状态进行评估和展示。案例机组的日常运行状态评估表明:所提方法可较SCADA系统提前发现机组发电机非驱动端轴承的异常,且误报次数较少。An improved degradation model is proposed to understand the operation conditions of wind turbines. Firstly,the degradation degree of each parameter in the hierarchical structure of wind turbine is calculated. Secondly,the weights of each state parameter and the parameter matrix are determined by an integrated method and the ridge type membership function respectively. Finally,the fuzzy comprehensive evaluation method and color images are used to evaluate and display the operating status of wind turbines. Results shows that the proposed method can detect the abnormal bearing at the non-drive end of wind turbine generator before the SCADA system,and the number of false alarms is less.

关 键 词：风电机组 状态评估 改进劣化度模型 综合评判 彩色图谱 

分 类 号：TK83[动力工程及工程热物理—流体机械及工程]