Adaptive Model Predictive Control for Fire Incidents in Water Distribution Networks

Abstract

The real-time control of water distribution networks for firefighting is an important but little-studied problem. Water utilities in England and Wales reduce hydraulic pressure to a minimum regulatory threshold in order to reduce leakage and avoid financial penalties. However, utilities are not legally bound to guarantee specific flow rates from fire hydrants, which poses a risk for firefighting. This study presents an adaptive nonlinear model predictive control scheme for water distribution networks integrating two modes of control: (1) normal control, when a network operates under normal conditions and the objective is to minimize energy costs and average zonal pressure, and (2) fire control, when fire flows need to be delivered from hydrants without exceeding maximum pressure and customer demand is maintained to the best extent possible. The proposed scheme is applied to an operational network. It demonstrates the combined benefits of reducing costs and leakage with increased fire flows.