Application of Multivariable Statistical Techniques in Plant-wide WWTP Control Strategies Analysis

Xavier Flores Alsina, J. Comas, I. Rodríguez-Roda, L. Jimémez, Krist Gernaey

Research output: Contribution to journalJournal articleResearchpeer-review


The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.
Original languageEnglish
JournalWater Science and Technology
Issue number6
Pages (from-to)75-83
Publication statusPublished - 2007


  • benchmarking
  • cluster analysis
  • control
  • discriminant analysis
  • principal component analysis
  • wastewater treatment

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