Application of the principal component analysis and cluster analysis in comprehensive evaluation of thermal power units

Abstract

In order to improve the operational level of safety, reliability, economy and environmental protection of thermal power units, the principal component analysis (PCA) and cluster analysis (CA) method were combined and proposed to assess the operating condition of fossil-fired power plants comprehensively, which can resolve the problem on the evaluation of multiple indicators. This method utilizes principal component analysis to perform the standardization, dimension-reduction and de-correlation of multiple evaluation indicators system for thermal power unit and abstracts the principal components. Moreover, the principal components were extracted as a new data matrix by cluster analysis. Finally the principal component scores and cluster classification were combined for comprehensive evaluation. It can provide the high reference value for the power generation group on how to implement energy saving, optimal operation, index evaluation and competition in thermal power units. The practical example shows that the proposed method is effective.