A MILP-based operational decision-making methodology for demand-side management applied to desalinated water supply systems supported by a solar photovoltaic plant: A case study in agricultural industry

In the field of water management, desalination industry has faced various economic and environmental challenges. Renewable energies and the incorporation of operational strategies such as demand-side management have been able to contribute with the aim of facing them. Nonetheless, it is necessary to continue studying demand-side management for water supply systems emphasising it as a strategic tool to make operational decisions. This article presents a methodology based on a novel Mixed-Integer Linear Programming model in order to program the operation of a seawater reverse osmosis desalination plant with one pumping station for a desertic remote agricultural zone, in accordance with the principles of demand-side management. A photovoltaic solar plant connected to the grid is considered as a renewable energy source. The mathematical model aims to establish the optimal hourly operating load of the system that minimises the daily margin of purchased electricity costs minus sales income of generated electricity. The case study where the methodology is tested is an agricultural area in Northern Chile. The proposed methodology in this paper establishes the basis for future research and industrial applications, considering that it can be generalised to other geographical situations, as well as being modifiable to be adapted for more complex water supply systems and/or other renewable energy sources.

Automated summary

This study proposes a methodology for the operation of a seawater desalination plant and a pumping station, based on demand-side management principles, using a novel Mixed-Integer Linear Programming model. The methodology considers the incorporation of a photovoltaic solar plant as a renewable energy source. The case study conducted in a agricultural area in Northern Chile establishes the foundation for future research and industrial applications.