Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis

被引：7

作者：

Flores, X. ^{[1
]}

Comas, J. ^{[1
]}

Roda, I. R. ^{[1
]}

Jimenez, L. ^{[2
]}

Gernaey, K. V. ^{[3
]}

机构：

[1] Univ Girona, Lab Chem & Environm Engn LEQUIA, Girona 17071, Spain

[2] Univ Barcelona, Dept Chem Engn, E-08028 Barcelona, Spain

[3] Tech Univ Denmark, Dept Chem Engn, DK-2800 Lyngby, Denmark

来源：

WATER SCIENCE AND TECHNOLOGY | 2007年 / 56卷 / 06期

关键词：

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

D O I：

10.2166/wst.2007.586

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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.

引用

页码：75 / 83

页数：9

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