State Estimation in Water Distribution Networks through a New Successive Linear Approximation

Abstract

State estimation (SE) of water distribution networks (WDNs) is difficult to solve due to nonlinearity/nonconvexity of water flow models, uncertainties from parameters and demands, lack of redundancy of measurements, and inaccurate flow and pressure measurements. This paper proposes a new, scalable successive linear approximation to solve the SE problem in WDNs. The approach amounts to solving either a sequence of linear or quadratic programs---depending on the operators' objectives. The proposed successive linear approximation offers a seamless way of dealing with valve/pump model nonconvexities, is different than a first order Taylor series linearization, and can incorporate with robust uncertainty modeling. Two simple testcases are adopted to illustrate the effectiveness of proposed approach using head measurements at select nodes.

Published in IEEE 58th Conference on Decision and Control, Nice, France, December 11--13, 2019