Abstract
This study starts by modeling and analyzing a smart combined energy system that includes a concentrated solar power plant, steam Rankine, Brayton, organic Rankine cycles, reverse osmosis unit, and a thermoelectric generator. The system is then subjected to bi-criteria optimization, using non-dominated sorting genetic algorithm II (NSGA-II) and minimizing annual costs and maximizing exergy efficiency. The system is located in Isfahan (central Iran) and intended to produce electricity and freshwater. The thermodynamic results indicated the most critical parameters affecting system performance: direct normal irradiance, number of heliostats, turbine efficiency and inlet temperature, compressor pressure ratio, and steam Rankine cycle pump inlet temperature. A Pareto frontier was charted, producing a set of optimal points, where a decrease in costs was achieved if the exergy efficiency was slightly compromised, leading to the identification of an optimal location within the Pareto frontier.
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