Estimation of real-time demands on the basis of pressure measurements by different optimization methods

The aim of the investigation, reported in this paper, was to estimate real-time demands in a water distribution system (WDS) on the basis of the pressure measurements. The task has been formulated as an optimization procedure which determines water fluxes that minimize differences between measured and modelled pressures. The Levenberg-Marquardt algorithm (LMA) and a genetic algorithm (GA) have been tested to solve the problem. The comparison showed that the LMA works much faster than the GA. The investigation showed also that the higher the demands, the lower is the sensitivity of the results to random errors in pressure measurements. All calculations have been accomplished using measurements executed in an operational WDS for different years and for different weekdays.