摘要
为及时准确地评估风电机组运行状态,结合集对分析和证据理论各自的特点提出了一种风电机组运行状态评估的新方法。该方法根据风电场数据采集与监控系统的物理量,构建机组运行状态评估的指标体系,建立了一个2层评价模型。模型第1层采用集对分析处理指标不确定性的劣化度,并生成模型第2层的基本概率分配。模型的第2层采用证据理论进行多证据融合,得到机组运行状态的隶属度,同时基于隶属度最大原则与信度准则共同评判风电机组运行状态等级。采用所提评估方法对某风电场1.5 MW并网风电机组进行状态评估,并将评估结果与传统的模糊综合评估方法得到的结果进行比较,结果表明所提评估方法的结果更准确,在状态的趋势分析中也表现较好。
A method of operating state assessment based on set-pair analysis and evidential reasoning decision-making is proposed to timely and accurately evaluate the operating state of wind turbine generator unit,which establishes an index system according to the physical variables of wind farm SCADA system and builds a two-layer assessment model. In the first layer,the set-pair analysis is adopted to deal with the deterioration degree of index uncertainty for generating the basic probability assignments for the second layer. In the second layer,the evidential reasoning decision-making is adopted to aggregate all the evidences for calculating the membership degree of unit operating state. Based on the maximum membership degree principle and the confidence criteria,the operating state of wind turbine generator unit is evaluated. The operating state of a 1.5 MW grid-connected unit is assessed by the proposed method and the results are compared with those by the traditional fuzzy comprehensive evaluation method,which shows that the proposed method has higher precise and better performance in the trend analysis of unit operating state.
出处
《电力自动化设备》
EI
CSCD
北大核心
2017年第7期38-45,共8页
Electric Power Automation Equipment
基金
国家重点基础研究发展计划(973计划)资助项目(2012CB215205)~~
关键词
风电机组
状态评估
集对分析
证据理论
联系度
风电
wind turbine generator system
state assessment
set-pair analysis
evidential reasoning decision-making
correlation
wind power
