Optimization techniques for coupling renewable/hybrid energy options with desalination systems for carbon footprint reduction

Abstract

In light of the global concerns for increased greenhouse gas (GHG) emissions, the industrial market is shifting towards more environmentally friendly processes, to meet strict emission standards. Although many studies have addressed the problem of carbon footprint reduction in desalination processes through the replacement of standard fossil fuel options with renewable energy sources, to date, none of these assessment methods have captured the effects of imposing different carbon reduction targets on the optimal design of desalination systems, and their respective energy sources. This paper proposes an optimization-based technique for the design of cost-effective desalination networks, integrated with renewable energy sources, subject to different carbon reduction targets. The presented methodology is capable of identifying optimum configurations for an integrated system that combines desalination options with renewable/hybrid energy technologies, whilst ultimately satisfying the water and energy demand that is required from the entire system. The importance of this approach lies in its ability to guide decision-making activities for such networks. A Mixed Integer Nonlinear Program (MINLP) has been proposed, which ultimately allows for the selection of the best mix between desalination technologies, and associated energy sources, based on a required carbon emission target. The proposed model has been illustrated using a case study, and the sensitivity of attained designs has been studied with respect to a number of key operating parameters.