Uncertainty Quantification of Water Distribution System Measurement Data based on a Least Squares Loop Flows State Estimator.

摘要: This paper presents a novel algorithm for uncertainty quantification of water distribution system measurement data including nodal demands/consumptions as well real pressure and flow measurements. procedure, referred to Confidence Limit Analysis (CLA), is concerned with deployment Least Squares (LS) state estimator based on the loop corrective flows variation demands independent variables. The confidence limits obtained pressures inflows/outflows network are determined called Error Maximization (EM) method evaluated respect two other more established CLA algorithms an Experimental Sensitivity Matrix (ESM) sensitivity matrix LS heads equations estimator. estimated networks show that proposed EM comparable benchmark but due its computational efficiency it suitable online decision support applications in systems. Both ESM methods work any operating point, whether arbitrarily or randomly chosen, although has advantage being computationally superior working sets