Model predictive control strategy of energy-water management in urban households

The management of energy-water nexus in buildings is increasingly gaining attention among domestic end-users. In developing countries, potable water supply is unreliable due to increasing demand, forcing end-users to seek alternative strategies such as pumping and storage in rooftop tanks to reliably meet their water demand. However, this is at an increased cost of energy cost. In this paper, the open loop optimal control model and the closed-loop model predictive control (MPC) model, both with disturbances, are compared while minimizing the maintenance cost of the pump. The open loop optimal model is suitable in instances where only random disturbances due to measurement errors are present. However, in case the demand pattern changes for reasons such as occupancy change in the house, the closed-loop MPC model is suitable as it robustly minimizes the pumping cost while meeting the customer demand. Further, MPC proves its robustness as it is able to overcome the turnpike phenomenon. Each of these two models has their own strengths. The open loop model is cost effective and easy to implement for customers that have a steady demand pattern while the closed-loop MPC model is more robust against demand pattern changes and external disturbances. It is recommended that these two models are adopted according to the specific application.