Desalination supply chain decision analysis and optimization

The desalination industry has been growing progressively in the last few decades. A large number of new plants are contracted every year. Strategic decisions related to plant locations and capacity, the selection of the desalination technology, and many other technical decisions related to the plant design and operation are very critical to these strategic investments. Viewing the desalination industry network as a supply chain provides a holistic view allowing decision makers to perform optimization of water desalination operations end to end. The methodology we propose provides the decision makers with (1) a set of investment alternatives comprising combinations of the different desalination locations, capacities, technologies, and energy sources, and (2) a decision graph showing the performance of each decision alternative in terms of quantitative and qualitative performance metrics chosen by the decision maker. The case study of Saudi Arabia, the world leader in desalination, shows how the methodology can present strategic planners with an optimal configuration of the desalination supply chain. © 2014 Elsevier B.V. All rights reserved.

We discussed the various decisions involved in the strategic planning of desalination options including the plant locations, technology type, capacities, operational considerations, distribution network structure and capacity, and environmental considerations. We also proposed a methodology which supports systematic decision making to optimize desalination options based on a formal optimization model that we implemented and used to solve for the case study of Saudi Arabia. Water resource planners and decision makers in Saudi Arabia can use the case study results and analysis as an aid in sustainable and economic development for desalination capacity expansions. Interesting future directions include modeling the complete water resource including, for example, ground and surface water to allow evaluation of other alternatives to meet water demand and to understand the real value of desalination in an integrated water resource planning model. In addition, one may also model the energy consumption of desalination including the unit level parameters to allow optimizing the performance on the desalination unit level. GIS infrastructure and utility network analysis and optimization tools can be used in further detail to build a more involved and fully integrated decision support system for water resource planners. Acknowledgment The authors would like to thank the King Fahd University of Petroleum and Minerals in Dhahran, Saudi Arabia, for funding the research reported in this paper through the Center for Clean Water and Clean Energy (CCWCE) at MIT and KFUPM under the Ibn Khaldun Fellowship. Special thanks to Prof. Mohammed A. Antar for his support providing valuable references and his expert opinion. The authors would like also to thank Effat University in Jeddah, Saudi Arabia for the sabbatical assistance provided to the first author.