Investigating the Role of Renewable Energies in Integrated Energy-water Nexus Planning under Uncertainty Using Fuzzy Logic

TL;DR

This paper explores how renewable energies can enhance sustainable energy-water nexus planning under uncertainty, using fuzzy logic to model variability and improve decision-making for future resource management.

Contribution

It introduces a fuzzy logic-based framework to incorporate uncertainty in renewable energy integration within energy-water nexus planning, highlighting its benefits and challenges.

Findings

Renewable energies can significantly improve nexus sustainability.

Fuzzy logic effectively models uncertainty in renewable energy scenarios.

Grid reliability depends on aligning renewable integration with system uncertainty.

Abstract

Energy and water systems are highly interconnected. Energy is required to extract, transmit, and treat water and wastewater, and water is needed for cooling energy systems. There is a rapid increase in demand for energy and water due to factors such as population and economic growth. In less than 30 years, the need for energy and water will nearly double globally. As the energy and water resources are limited, it is critical to have a sustainable energy-water nexus framework to meet these growing demands. Renewable energies provide substantial opportunities in energy-water nexuses by boosting energy and water reliability and sustainability and can be less water-intensive than conventional technologies. These resources, such as wind and solar power, do not need water inputs. As a result, they can be used as a supplement to the energy-water nexus portfolio. In this paper, renewable energies in energy-water nexus have been investigated for a range of possible scenarios. As renewable energy resources are not deterministic, fuzzy logic is used to model the uncertainty. The results show that renewable energies can significantly improve the energy-water nexus planning; however, the power grid reliability on renewable energy should be aligned with the level of systems uncertainty. The gap between the decisions extracted from the Fuzzy model and the deterministic model amplifies the importance of considering uncertainty to generate reliable decisions. Keywords: Energy-water Nexus, Renewable Energies, Optimization under Uncertainty, Fuzzy Logic.