Access to fresh water is a major human right as mankind existence depends on it. The balance between fresh water supply and actual water demand for agricultural purposes (irrigation) relies on the availability of fresh water in the underground aquifers or surface water resources. Water resources are under great pressure due to the high demand for irrigation to sustain crop productivity and cover domestic use as a result of demographic growth. Desalination of sea or brackish water is one of the solutions to provide water for irrigation in remote areas of limited freshwater reserves. In such areas, if desalination is powered by renewable energy sources, then it can become a lot more sustainable. This paper presents the development of an innovative computational tool for the optimal (economically and technically) design of seawater reverse osmosis desalination systems for sustainable water production for crop irrigation. In order to further reduce the cost of water produced, an energy management and control system was also designed and included in the computational tool to ensure the optimal operation of the desalination plant. This system allows the seawater reverse osmosis unit to operate at variable load and determines its optimal operation point using computational intelligence techniques based on fuzzy cognitive maps. According to the results, the implementation of the computational tool for the design of PV-SWRO system presents the lowest cost as compared to the system designed with the conventional methodology.

RO desalination, PV systems, Computational intelligence