Title: Multi-objective optimal design of solar-gas turbine driven polygeneration system based on 4E analysis
Authors: Khodadoost Rostami Zadeh; Seyed Ali Agha Mirjalily; Seyed Amir Abbas Oloomi; Gholamreza Salehi; Mohammad Hasan Khoshgoftar Manesh
Addresses: Department of Mechanical Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran ' Department of Mechanical Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran ' Department of Mechanical Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran ' Department of Mechanical Engineering, Faculty of Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran ' Energy, Environment and Biologic Research Lab. (EEBRlab), Division of Thermal Sciences and Energy Systems, Department of Mechanical Engineering, Faculty of Technology and Engineering, University of Qom, Qom, Iran; Center of Environmental Research, University of Qom, Qom, Iran
Abstract: In this paper, a novel polygeneration system for an office building based on an integrated flat plate solar collector and gas turbine to produce simultaneous power, freshwater, cooling and heating has been introduced. The proposed system includes a heat recovery steam generator, a multi-effect desalination (MED), reverse osmosis (RO), a steam turbine, a solar plate collector and an absorption chiller. The transient simulation and analysis for the solar system have been done in TRNSYS software. Also, a computer code was built to compute energy, exergy, exergoeconomic and exergoenvironmental (4E) analysis dynamically. Furthermore, multi-objective optimisation process using genetic algorithm (MOGA) and water cycle approach (MOWCA) to maximise the exergy efficiency, minimise the total cost of exergy and minimise the total environmental impacts of exergy has been conducted simultaneously. Genetic programming has been employed to generate correlations for objective function estimation with high accuracy for reducing computation time. Results show the overall exergetic efficiency, which is improved by 12.65% and 12.67% using MOGA and MOWCA. Also, the overall exergoeconomic cost of power and water is reduced by 27.66%, 32.97%, 27.83% and 32.96% using MOGA and MOWCA, respectively.
Keywords: polygeneration; exergetic; exergoeconomic; exergoenvironmental; water cycle algorithm.
International Journal of Exergy, 2022 Vol.37 No.3, pp.243 - 280
Received: 11 Dec 2020
Accepted: 16 May 2021
Published online: 16 Feb 2022 *