Co-Optimization and Community, Community Solar and RWH

This project investigated solar and RWH were more affordable when invested in as a community and if water and solar complemented each other. It created a new custom optimization scheme that takes into account a demand profile for energy and water. This project highlights the power of medium scale modeling to investigate novel research questions.

Abstract: Distributed water and energy technologies have the potential to reduce reliance on centralized infrastructures, household utility bills, and carbon footprints. Current adoption levels remain low because of issues such as long payback periods, limited consumer awareness, capital constraints, and resource intermittency challenges. In this study, we assess the ability of two system design concepts to improve the economics of distributed water and energy technologies, and ultimately encourage their broader adoption: (1) co-optimizing water and energy technology investments and operations, and (2) investing in community-scale rather than home-scale systems. We explore the benefits of these approaches by formulating a mixed-integer linear program for optimal system design and dispatch. Our case study applies this model to a neighborhood in Austin, Texas. Results show that distributed electricity and water production increase, and total cost decreases, when resources and demands are pooled at larger community scales. These community-scale systems make a wider range of technologies economically viable and enable greater asset utilization due to systems integration. The cost and carbon emissions reduction benefits of co-optimizing distributed water and energy investments are significant, especially at higher aggregation levels. While distributed water production alone tends to increase carbon emissions, complementing it with appropriate distributed electricity generation technologies can yield simultaneous economic and environmental benefits.

https://doi.org/10.1016/j.scs.2020.102515