Enhancing Knowledge in Water Distribution Networks via Data Assimilation

摘要: This paper deals with uncertainty estimation and knowledge enhancement in water distribution networks (WDNs). A new three steps data assimilation approach is introduced, which combination multi-objective optimization, allows selecting effective affordable monitoring networks. An innovative cascade of Ensemble Kalman Filters used to assimilate the information deriving from sensors measuring pressure heads, flow pipes demands, objective increasing while preserving at same time structural relationships among state variables. Selection most appropriate economically measurement network, then based on derivation a Pareto front using NSGA-II algorithm conjunction approach. The obtained by compromising between overall cost reduction (or enhancement), expressed as function Total Variance operational use proposed well effectiveness chosen observation network also demonstrated showing successive assimilations real-time observations.