Tracing the Dependency of Water and Energy in Smart and Connected Communities Through a Multi-domain Modeling Framework

Essential needs such as electricity generation, water distribution, and water treatment account for 12.6% of US energy consumption, of which water distribution (3.15%) is highly energy-intensive with the average energy use of 1300 kilowatt-hours per million gallons (kWh/MG). Water Distribution Networks (WDNs) are promising candidates for providing demand response due to the large fluid inertias, pressurized piping networks, and high energy intensity associated with pumping. However, to take advantage of the demand response potential of WDNs, we need to better understand the operation of community-level water networks and ways of energy optimization in connection with electricity operation. In this paper, we develop component and system models of community-level WDN using equation-based object-oriented Modelica language. Further, we exhibit the water-energy interdependencies through demand response (DR) pump controls based on time-of-use and critical-peak energy pricing as well as the commonly used tank level-based pump control using the developed modeling package. The DR pump controls exhibit a 25–29% energy savings and 17–27% cost savings compared to the commonly used pump control. This research has the potential to support dynamic modeling and optimization, demand response, resiliency analysis, and integrated decision-making in future smart and connected communities.