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中文摘要：
为解决火电厂运行优化、状态监测和故障诊断中机组运行状态的综合评价问题，在分析评价指标特点的基础上，将信息熵理论与主成分分析方法相结合应用于火电机组综合评价，得到了机组状态评价的二级指标和一级综合评价指标。以2008年全国600Mw火电机组竞赛中的5台机组为研究对象，建立基于信息熵与主成分分析的机组状态综合评价模型。该方法得到的机组排名与实际竞赛机组排名完全一致，表明该方法可信度和有效性较高，对不同机组进行状态对比和不同电厂之间开展竞赛具有较好的指导意义。
英文摘要：
Aimed at solving the comprehensive evaluation questions about optimal operation, condition monitoring and fault diagnosis in thermal power plant, and on the basis of analyzing the characteristics of evaluation indicators, information entropy theory and principal component analysis （PCA） method were combined and applied in comprehensive evaluation of thermal power plant units, then secondary evaluation indicators and first-class comprehensive evaluation indicators were obtained. Taken five units from 600 MW units in 2008＇s competition as the research objects, the comprehensive evaluation model based on information entropy and principal component analysis was established. The units rankings obtained by the method proposed in the paper are completely in conformity with the units rankings of actual competition, which indicates that the reliability and effectiveness of the method presented are high. The method presented could give guidance for processing unit state comparison among different traits and launching competition between different power plants.
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