Renewable Energy Resources and Technologies
Hediyeh Safari; Fateme Ahmadi Boyaghchi
Abstract
This research is concerned with the design and analysis of a geothermal based multi-generation system by applying both conventional and advanced exergy and exergoeconomic concepts. The proposed energy system consists of a dual-organic Rankine cycle (ORC) to vaporize liquefied natural gas (LNG) and produce ...
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This research is concerned with the design and analysis of a geothermal based multi-generation system by applying both conventional and advanced exergy and exergoeconomic concepts. The proposed energy system consists of a dual-organic Rankine cycle (ORC) to vaporize liquefied natural gas (LNG) and produce electricity. A proton exchange membrane(PEM) electrolyzer is employed to produce hydrogen by receiving the power and coolant heat waste of dual ORC. Moreover, cooling effect is produced during LNG regasification by utilizing the cryogenic energy of LNG. Parametric studies are conducted to assess the effects of substantial input parameters, namely turbine 1 inlet pressure, mass rate of upper cycle, geothermal mass flow rate, on the various parts of exergy destruction and cost rates within the major components.
Vajiheh Sabeti; Fateme Ahmadi Boyaghchi
Abstract
This paper deals with a multi-objective optimization of a novel micro solar driven combined power and ejector refrigeration system (CPER). The system combines an organic Rankine cycle (ORC) with an ejector refrigeration cycle to generate electricity and cold capacity simultaneously. Major thermodynamic ...
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This paper deals with a multi-objective optimization of a novel micro solar driven combined power and ejector refrigeration system (CPER). The system combines an organic Rankine cycle (ORC) with an ejector refrigeration cycle to generate electricity and cold capacity simultaneously. Major thermodynamic parameters, namely turbine inlet temperature, turbine inlet pressure, turbine back pressure, and evaporator temperature are selected as the decision variables. Three objective functions, namely the energetic efficiency, exergetic efficiency and cost rate of products are selected for optimization. NSGA-II and MOPSO are employed and compared, to achieve the final solutions in the multi-objective optimization of the system operating. It is found that the values of the energetic and exergetic efficiencies increase within 27.7% and 26.1%, respectively and the cost rate of products decreases by about 32.7% with respect to base case.
Mahboobe Sabaghian; Fateme Ahmadi Boyaghchi
Abstract
Energy, exergy and exergoeconomic (3E) evaluation are performed to assess the performance of a NH3/H2O cycle integrated with parabolic trough solar collectors (PTSC). To provide continuous electricity produced by generator when solar beam radiation is insufficient a stabilizer temperature subsystem is ...
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Energy, exergy and exergoeconomic (3E) evaluation are performed to assess the performance of a NH3/H2O cycle integrated with parabolic trough solar collectors (PTSC). To provide continuous electricity produced by generator when solar beam radiation is insufficient a stabilizer temperature subsystem is utilized. The major thermodynamic parameters and climate conditions variations are selected to investigate, for their effects on the energy efficiency, exergy efficiency and unit cost of electricity of the overall system. The results reveal that the solar collectors exhibit the worst exergy and exergoeconomic performance, so that when system is only fuelled by solar energy, elevation of solar beam irradiation around 40% reduces the efficiencies and electricity production cost within 23% and 0.4%, respectively. It is found that the increment of ammonia basic concentration, turbine inlet pressure, evaporator inlet temperature and evaporator pinch temperature lead to elevation of energy and exergy efficiencies and decrement of electricity production cost. Then, the single and multi-objective optimizations are performed to maximize the energy and exergy efficiencies and minimize the electricity production cost based on genetic algorithm (GA). Results indicate that the electricity production cost obtained through economic optimization is less than around 2% and 2.2% compared to the optimization based on the first and second laws of thermodynamics. Multi objective optimization causes reduction of electricity production cost around 14% and enhancement the energy and exergy efficiencies 8.5% and 6.7%, respectively too.