Artificial Intelligence Enabling Water Desalination Sustainability Optimization

Abstract

Recently, water desalination has been developing increasingly worldwide. Many new plants are contracted constantly. Strategic planning and many other technical decisions are significant to these strategic systems. The proposed Artificial Intelligent (AI) methods provide decision makers with different choices for investment, where each is comprised of different desalination combinations regarding to locations, capacities, and energy sources in terms of several performance metrics. The intelligent decisions determine the optimal stations location and the water desalination system capacity for future expectations. Other smart decisions select the optimal desalination technologies for available existing and suggested desalination planting. In addition, AI methods provide decision makers to configure the pipeline network and transport water among the planting locations. The proposed work is a method to upkeep strategic decision making for the best water desalination facility. Our methodology offers a set of AI alternatives for several desalination plans. Decision support systems and tools are imperfect to deliver a set of alternatives. Therefore, the proposed work provides a systematic decision process to validate several water desalination alternatives, considering intelligent water pumping to the locations through the pumping network and water storage at every location. The proposed approach is validated for a case study in Jordan, which is a beginner country in desalination. The results show where economic and environmental benefits occurs. It shows how the AI methods can introduce an optimal settings of the desalination process to the peopole who makes decisions.