A New Algorithm for the Design of Site Utility for Combined Production of Power, Freshwater, and Steam in Process Industries

JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME(2022)

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Abstract
Site utility, without a doubt, is one of the major units in process industries that consumed a lot of fossil fuels and significantly emitted emission pollution. In this paper, a systematic procedure was proposed to optimize the utility system's design and integration based on a targeting approach as process integration technique, exergetic, exergoeconomic, exergoenvironmental analysis associated with life cycle assessment (LCA), and multi-objective optimization through water cycle and genetic algorithms. Total site analysis was performed to provide an essential understanding of the equipment's characteristics and interactions in the site utility system. It also aims for power production and the temperature of the boiler and each steam level with acceptable accuracy. Furthermore, the exergetic, exergoeconomic, and exergoenvironmental analyses were presented to declare the effects of irreversibility, economic, and environmental impacts on the system. In this paper, to show the proposed method's applicability, the optimal design of a site utility associated with a petrochemical complex has been considered. First, the optimal design is performed based on minimization of total annualized costs (TAC) as one-objective function through star software, genetic algorithm (GA), water cycle algorithm (WCA), proposed GA, and proposed WCA method. In the next phase, the optimal design is done based on MOGA, MOWCA, proposed MOGA, and proposed MOWCA methods based on maximum exergetic efficiency, and freshwater production, and minimization of exergetic cost, and total environmental exergetic impact. Results show by using the new procedure, the optimum solution has been achieved by a significant reduction of computational time.
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Key words
new procedure, site utility, targeting, exergy, exergoeconomic, exergoenvrionmental, water cycle algorithm, energy systems analysis, power (co-) generation, renewable energy
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