The U.S. electricity grid's ongoing transformation to integrate renewable or distributed generation, address aging infrastructure, and improve grid resilience and reliability all motivate increasing the base of available demand-side resources that offer services to the grid. Water systems have several characteristics relevant to increasing the amount of demand-side services provided to the electric grid, including unique physical and chemical properties, location within urban areas, inextricable linkages between energy and water use, and untapped potential in the space. This research addresses opportunities to provide two types of demand-side service from within the water sector: load management and energy efficiency.

Improved pump scheduling at municipal pump stations was explored in a case study to quantify the influence of electric rate design on the amount of load management that water utilities can affordably provide. The analysis found significant potential for electric and water utilities to cooperate on rate design and load scheduling, and that rate structure is a key enabler of mutually beneficial arrangements.

Environmental and economic impacts of community-scale water recycling were addressed through the formulation of an optimal capacity and dispatch model. The model was demonstrated in a case study, which found that the community-scale system can be economically feasible in certain areas and might significantly decrease reliance on central water utilities, but that relying on grid electricity will significantly increase demand and associated emissions. The results motivate exploration of community-scale systems within microgrids with increased availability of renewable energy.

In the residential sector, very high sampling rate data is used to develop machine learning classifiers to categorize end use water events by appliance type. Classifier performance is shown to improve with the addition of coincident electricity data and dedicated sub-meter data. Results from this work have potential to improve customer awareness of water use and facilitate adoption of efficient appliances or conservation behaviors. This work is extended via a spatio-economic analysis of cost effectiveness for residential water-related appliance retrofits. The analysis unites novel data sets to create an interactive online tool that allows users to evaluate energy savings and avoided emissions based on heterogenous usage, behavioral parameters, and geographic factors.

Together, this body of research identifies promising opportunities for new technology, operational strategies, and policies within the water sector to support ongoing transformation towards a cleaner, responsive, and resilient electric grid.