(317c) Systematic Analysis and Optimization of Water-Energy Nexus

The importance of the water-energy nexus is well known [1]. For example, power plants need water to generate energy and desalination plants need energy from power plants to produce freshwater. While power plants are energy sources and water sinks, desalination plants are water sources and energy sinks. From plants to regions to countries, sources and sinks coexist and interact by exchanging energy and water. The net input in this nexus is the total energy and water withdrawn from natural resources, such as underground fossil fuels, fresh water reserves, and so on. The net outputs from the nexus are the ones that satisfy societal demands. The dynamic behavior of energy/water demands, the presence of multiple networks, and the complex interactions between various sources and sinks greatly affect decision making within a water-energy nexus [2]. Therefore, a systematic and holistic analysis of a nexus is critical.

This work focuses on understanding the interconnection of water and energy flows and optimizing the energy-water networks within a nexus. We present two systematic strategies for the analysis and optimization of a nexus. The first approach relies on a novel representation of different sources and sinks using a single energy vs. water load diagram. This diagram enables the development of a graphical procedure, similar to classical pinch analysis [3,4] for source-sink integration, capable to (i) identify redundant networks within a nexus, (ii) minimize the total energy and water production, while providing the same energy and water grid supplies, and (iii) to maximize the energy and water grid flows from an existing infrastructure. The second is an algebraic approach that includes mathematical models to represent a water-energy nexus. Specifically, we propose a linear programming transshipment-based model, similar to [4], for water-energy nexus optimization. The LP formulation can be further extended to a mixed-integer nonlinear optimization (MINLP) formulation to include capital, operating and transportation costs. This approach provides an optimal network design in terms of minimum number of plants, minimum network cost, or maximum grid flows. Finally, the two approaches with various objectives are implemented on real cases studies at regional, state and country levels.

References

[1] Garcia, D. J. and F. You (2016). "The water-energy-food nexus and process systems engineering: A new focus." Computers & Chemical Engineering 91: 49-67.

[2] Carter, N. T. (2011). Energy’s water demand: trends, vulnerabilities, and management, DIANE Publishing.

[3] Linnhoff, B. and E. Hindmarsh (1983). "The pinch design method for heat exchanger networks." Chemical Engineering Science 38(5): 745-763.

[4] El‐Halwagi, M. M. and V. Manousiouthakis (1989). "Synthesis of mass exchange networks." AIChE Journal 35(8): 1233-1244.

[5] Papoulias, S. A. and I. E. Grossmann (1983). "A structural optimization approach in process synthesis—II: Heat recovery networks." Computers & Chemical Engineering 7(6): 707-721.