针对火电机组运行状态评价中涉及到的多指标体系的综合评价问题,本文将主成分分析和聚类分析相结合应用于机组运行状况综合评价.首先运用主成分分析法对单一指标评价体系进行综合,抽取影响火电机组运行状况的主要因素;然后以提取出的主成分作为新的数据矩阵进行聚类分类,避免了经典聚类定性选择聚类变量的主观性;最后利用主成分得分的大小来量化各因素的优劣性,评价结果全面地反映了机组的整体运行状况.实例分析结果验证了本文所提方法的有效性.%In order to solve the problem of comprehensive evaluation for multi-indicator system involved in operation state evaluation of thermal power units,the principal component analysis and cluster analysis are combined and applied to the comprehensive evaluation of power units.This method utilizes the principal component analysis to perform dimension-reduction,standardization and decorrelation for unit operation indicators,then the principal components affecting the unit operation state are extracted.Moreover,the extracted principal components are considered as a new data matrix for cluster analysis,which avoids the disadvantage of subjectivity of the classical clustering method when choosing the clustering variables.Finally,the principal component scores and the cluster classification are combined for the comprehensive evaluation.The case study result verified the effectiveness of the above method.
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