Computational Intelligence in the Desalination Industry

Pedro Cabrera () and José A. Carta ()
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Pedro Cabrera: University of Las Palmas de Gran Canaria
José A. Carta: University of Las Palmas de Gran Canaria

Chapter Chapter 5 in Computational Intelligence and Optimization Methods for Control Engineering, 2019, pp 105-131 from Springer

Abstract: Abstract Numerous studies have been undertaken since the start of the 1990s—when various authors began to propose the use of artificial intelligence in the field of water desalination—on the employment of computational intelligence (CI) systems in this technological field. The main goal of the proposals put forward has been to tackle the high degree of complexity involved in the different processes that can be found in the desalination industry. The wide variety of topics suggested as potential candidates for the application of CI in desalination processes include, among others, alarm processing and fault detection, control systems, operational optimization applications, load forecasting and security assessment. Although desalination plants have traditionally been powered by energy supplied by the burning of fossil fuels, there is a growing trend today, for various reasons, to use renewable energy sources to directly power these plants. This has added new challenges to the management of desalination processes as the temporal variability of renewable energy sources makes the decision-making processes more complicated. In turn, this means that a multivariable approach is required to ensure optimal desalination plant operation by maximizing the exploitability of the variable renewable resource. This chapter presents a review of how CI systems have been used to date in the desalination industry. A special mention is given to new developments which use CI systems to help overcome newly emerging challenges related to the increasing usage of renewable energy sources in the powering of desalination processes.

Date: 2019
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DOI: 10.1007/978-3-030-25446-9_5

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