A novel solar-biomass based multi-generation energy system including water desalination and liquefaction of natural gas system: Thermodynamic and thermoeconomic optimization. (20th September 2018)

• Record Type: Journal Article
• Authors: Ghasemi, Amir; Heidarnejad, Parisa; Noorpoor, Alireza
• Is Part Of: Journal of cleaner production. Volume 196(2018)
• Page Start: 424
• Page End: 437
• Publication Date: 2018-09-20
• Subjects: Multi-generation energy system -- Exergy -- Thermoeconomic -- Desalination -- Liquefaction of natural gas system; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2018.05.160
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: In this study, an inventive multi-generation energy system utilizing solar and biomass energy as a complementary fuel are proposed and analyzed, by means of a thermodynamic and thermoeconomic investigation and multi-objective optimization. For supplying electricity, heating and cooling power, a Rankine cycle including a turbine, a heater and a double effect absorption chiller, for liquefaction of natural gas, a Linde-Hampson cycle, for desalination of sea water, a multi-effect desalination system, for solar energy exploitation, a parabolic Trough solar collector and for combustion of biomass, a burner is utilized. Results outline that, the studied system has potential to generate 16.11 kW electricity, 28.94 kW heating power, 23.41 kW cooling power, 8.8 kg/h fresh water and 0.02 m 3 /h liquefied natural gas with the energy and exergy efficiencies of 46.8%, 11.2%, and product cost rate of 15.16 $/h. A comprehensive modeling is accomplished by applying mass, energy, exergy and thermoeconomic balances to all component of the multi-generation energy system. The investigation becomes more comprehensive with a sensitivity analysis in order to survey the dependency of the thermodynamic and thermoeconomic performance upon the decision variables such as stack gasses temperature, temperature difference of evaporator1, evaporator2 temperature and Turbine inlet temperature. Finally, optimized performance of the system is determined using Genetic Algorithm and deriving Pareto front considering the exergy efficiency and product cost rate as objective functions. The optimized multi-generation energy system could yield the exergy efficiency of 9.9% and the product cost rate of 13.32 $/h.