Optimization of water-energy-food nexus via an integrated system of solar-assisted desalination and farming

This paper introduces a systematic framework for water-energy-food (WEF) nexus with focus on integrating water desalination (via reverse osmosis and thermal desalination), energy generation (from fossil-based power plants and solar panels), and crop production. Specifically, the paper provides the provides generally applicable and new contributions in formulating WEF nexus problems as multi-objective, multi-period optimization problems with data-driven models based on field work. The paper also established a systematic method for integrating and reconciling farming methods, water technologies, energy-resource selection and operation, carbon footprint, and economic factors. A superstructure representation is used to embed the candidate options and configurations. An optimization formulation is developed to determine the optimal system configuration, water and energy uses and sources, and crop mix selection. A multi-period model is developed to account for the seasonal variability. The optimization model is solved under different carbon-footprint cuts to establish a tradeoff curve between the economic and environmental objectives. To generate the necessary experimental data for a meaningful case study, a year-long field study was carried out to generate experimental data for three fields were constructed in Kuwait using open-field, agrivoltaic, and greenhouse farming methods. The field data were extracted and coupled with the optimization formulation to apply the proposed approach to a case study. First, the optimization formulation was solved to maximize the net profit with no limits on the carbon footprint. The solution of this relaxed formulation gives a maximum profit of 2.127 MM USD/y and an annual emission of 2242 tonne CO2eq. Next, the optimization formulation was solved with the objective of minimizing the total annual emissions. The result was a minimum annual emission of 363 tonne CO2eq that corresponded to 1.366 MM USD/y of profit. The ɛ-constraint method was employed to establish tradeoffs between the economic and environmental objectives. The solutions also provided valuable information on the percentage contribution of solar energy and water sources.