An energy and cost efficiency Model Predictive Control framework to optimize Water Supply Systems operation

Water utilities face new challenges in adapting to the energy transition, marked by the rise of renewable generation, flexible loads and more dynamic energy markets. This transition also offers opportunities for more sustainable water supply operational management. Recently, Model Predictive Control (MPC) has gained interest in water supply system (WSS) management due to its ability to incorporate forecasting, such as water demand and renewable generation, into real-time optimal control operations; yet its adoption within the water sector remains limited and validation is lacking. This paper presents an MPC framework to minimize energy costs in WSS, integrating features like time-differentiated energy prices, on-site renewable generation, and energy storage systems. The main original contribution of this work lies in the development of a MPC framework that simultaneously considers multiple energy resources in the optimization of WSS operation. Validation on a real-world water network demonstrates significant potential savings (around 32% in WSS operation costs), thereby highlighting the role of MPC in assisting real-time decision-making for efficient operation of water utilities contributing to the energy transition.