A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective Optimization

• Published in: Sustainability Vol. 13; no. 11; p. 6448
• Main Authors: Hamrang, Farzad, Mahmoudi, S. M. Seyed, Rosen, Marc A.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2021
• Subjects: Alternative energy sources; Availability; Biomass; Cogeneration; Combustion chambers; Cost control; Desalination; Efficiency; Electricity; Energy resources; Exergy; Fresh water; Gas turbines; Gases; Gasification; Heat; Heat recovery systems; Hybridization; Multiple objective analysis; Neural networks; Optimization; Payback periods; Reliability analysis; Subsystems; Sustainability; Synthesis gas; Thermodynamics; Turbines
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su13116448

Based on the benefits of integrated gasification combined cycles (IGCCs), a cogeneration plant for providing electricity and freshwater is proposed. The main novelties of the devised system are the integration of biomass gasification and a regenerative gas turbine with intercooling and a syngas combustor, where the syngas produced in the gasifier is burned in the combustion chamber and fed to a gas turbine directly. The energy discharged from the gas turbine is utilized for further electricity and freshwater generation via Kalina and MED hybridization. The proposed system is analyzed from energy, exergy, exergoeconomic, and reliability–availability viewpoints. The optimal operating condition and optimum performance criteria are obtained by hybridizing an artificial neural network (ANN), the multi-objective particle swarm optimization (MOPSO) algorithm. According to results obtained, for the fourth scenario of the optimization process, optimal values of 45.10%, 14.27 kg·s−1, 12.95 USD·GJ−1, and 8141 kW are obtained for the exergy efficiency, freshwater production rate, sum unit cost of products, and net output power, respectively. According to reliability and availability assessment, the probability of the healthy working state of all components and subsystems is 88.4403%; the system is shown to be 87.74% available of the time over the 20-year lifetime.