{"title":"Confidence Limit Analysis of Water Distribution Systems Based on a Least Squares Loop Flows State Estimation Technique","authors":"Corneliu T. C. Arsene, D. Al-Dabass, J. Hartley","doi":"10.1109/EMS.2011.11","DOIUrl":null,"url":null,"abstract":"This paper presents a novel algorithm for uncertainty quantification in water distribution systems, which is termed also Confidence Limit Analysis (CLA), in the context of a Least Squares (LS) state estimator based on the loop corrective flows and the variation of nodal demands as state variables. The confidence limits predicted with the novel algorithm called Error Maximization (EM) method are evaluated with respect to two other more established CLA algorithms based on an Experimental Sensitivity Matrix (ESM) and on a sensitivity matrix obtained with the LS nodal heads equations state estimator. The predicted confidence limits show that the novel EM algorithm is comparable to the other CLA algorithms shown in the paper and due to its computational efficiency renders it suitable for online decision support systems for water distribution systems.","PeriodicalId":131364,"journal":{"name":"2011 UKSim 5th European Symposium on Computer Modeling and Simulation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 UKSim 5th European Symposium on Computer Modeling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EMS.2011.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper presents a novel algorithm for uncertainty quantification in water distribution systems, which is termed also Confidence Limit Analysis (CLA), in the context of a Least Squares (LS) state estimator based on the loop corrective flows and the variation of nodal demands as state variables. The confidence limits predicted with the novel algorithm called Error Maximization (EM) method are evaluated with respect to two other more established CLA algorithms based on an Experimental Sensitivity Matrix (ESM) and on a sensitivity matrix obtained with the LS nodal heads equations state estimator. The predicted confidence limits show that the novel EM algorithm is comparable to the other CLA algorithms shown in the paper and due to its computational efficiency renders it suitable for online decision support systems for water distribution systems.