Water-Energy Nexus in Smart Microgrids: A Day-Ahead Scheduling Model with Uncertainty Management

The increasing interdependence of water and energy systems in smart microgrids necessitates integrated management strategies to enhance sustainability and cost efficiency. This study presents a day-ahead scheduling model that co-optimizes water and energy resources while addressing uncertainties in renewable generation, demand, and system constraints. The proposed model builds upon the water-energy co-optimization framework, extending its applicability to uncertainty management in community-scale microgrids. The model incorporates distributed energy resources, energy storage, wastewater treatment, and municipal water interactions. It utilizes stochastic optimization techniques to handle uncertainties in renewable generation and water availability, ensuring robust scheduling decisions. A benchmark case, which assumes water is solely supplied from municipal sources without local management, is compared with the proposed water-energy co-optimized approach. Simulation results demonstrate that integrating water-energy scheduling significantly reduces operational costs by leveraging local wastewater treatment and energy storage strategies. Compared to conventional microgrid energy management, the proposed approach achieves a cost reduction of approximately 6.66%, primarily by optimizing water distribution and treatment alongside energy dispatch.