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Abbas Rezaei

Abbas Rezaei

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty ofٍٍ Electrical Engineering
Address:
Phone: 083-38305001

Research

Title
Artificial neural network multi-objective optimization of a novel integrated plant to produce power, cooling and potable water
Type
JournalPaper
Keywords
Geothermal energy Multi-generation Neural network Optimization
Year
2022
Journal Energy for Sustainable Development
DOI
Researchers Tao Hai ، Salah I. Yahya ، Jincheng Zhou ، Ibrahim B. Mansir ، Abbas Rezaei ، Kabir Al Mamun

Abstract

This article investigates a geothermal energy-based cycle to produce power, cooling, and fresh water, using humidification-dehumidification technology. Energy, exergy, and exergo-economic analysis have been performed for a geothermal cycle and a proposed cycle that is an improvement of the basic cycle. Comparative analysis for the new cycle has been extracted and exergy-economic parameters have also been calculated.Moreover, by using artificial neural network and multi-objective optimization, optimal parameters of the system have been extracted. The primary novel part of this study is that different subsystems combined in a way generate different products and the optimum performance parameters are introduced based on the multi-objective optimization. The obtained results show that the highest exergy destruction is related to heat exchanger 1 (HX1) with a value of 670.5 kW. The proposed systemcan produce 1.104 kg/s freshwater and its net power production capacity is 2251kW. Also, the exergy destruction in the proposed systemis 964.4kWhigher than the basic cycle. Based on the multi-objective optimization, the optimal point is selected based on the ideal result of 32.35 % efficiency and 2322.32 kW exergy destruction, and the parameter unit cost of product is 8.81 $/kW