Author(s): H. Awad; A. Kawamura; K. Jinno

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Keywords: Water Supply Network; Kalman filter; On-line prediction; Water demands

Abstract: This paper presents a method for on-line prediction of nodal water demands in a supervisory water supply network. Based on Kalman filtering theory, the developed prediction algorithm had used two equations in the simulation of water supply network, the continuity equation and the head loss equation after being linearized using Taylor expansion series. The observable variables in Kalman filter algorithm are recorded from flow meters and pressure gauges which are connected to the pipes and nodes of the network. To investigate the performance and accuracy of this technique, this prediction method was applied to a certain block of Fukuoka City water supply network. As Kalman filter parameters are variable with time, results had shown the efficiency of this technique in the prediction of all nodal demands in the studied water supply network and thus decrease the uncertainty in determining the values of these quantities. On the other hand, predicted on-line values of water supply network variables as pipe discharges and hydraulic pressures are calculated in parallel with the computation of nodal demands. With the highly accurate results obtained from applying Kalman filter technique in the field of on-line prediction, a promising improvement of the existing water supply models is expected.

DOI:

Year: 2003