Minimizing the Effect of Substantial Perturbations in Military Water Systems for Increased Resilience and Efficiency

Abstract

Abstract:A model predictive control (MPC) framework, exploiting both feedforward and feedback control loops, is employed to minimize large disturbances that occur in military water networks. Military installations' need for resilient and efficient water supplies is often challenged by large disturbances like fires, terrorist activity, troop training rotations, and large scale leaks. This work applies the effectiveness of MPC to provide predictive capability and compensate for vast geographical differences and varying phenomena time scales using computational software and actual system dimensions and parameters. The results show that large disturbances are rapidly minimized while maintaining chlorine concentration within legal limits at the point of demand and overall water usage is minimized. The control framework also ensures pumping is minimized during peak electricity hours, so costs are kept lower than simple proportional control. Thecontrol structure implemented in this work is able to support resiliency and increased efficiency on military bases by minimizing tank holdup, effectively countering large disturbances, and efficiently managing pumping.

Special Issue on Feature Papers for Celebrating the Fifth Anniversary of the Founding of Processes

“…The Special Issue contains two papers in this section, both focused on water systems. The first contribution presents a combined feedforward/feedback model predictive control strategy for minimizing disturbance effects in military water networks [18]. The second contribution investigates the problem of optimal capacity planning in seawater desalination systems from a multiscale perspective [19].…”