4E analysis and three-objective optimization for selection of the best prime mover in smart energy systems for residenti
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4E analysis and three‑objective optimization for selection of the best prime mover in smart energy systems for residential applications: a comparison of four different scenarios Ehsan Gholamian1 · Pedram Hanafizadeh1 · Pouria Ahmadi1 · Livio Mazzarella2 Received: 8 June 2020 / Accepted: 7 August 2020 © Akadémiai Kiadó, Budapest, Hungary 2020
Abstract Recently, using integrated energy systems for residential-scale applications has been of great interest to the researchers. The objective of this study is the proposal, techno-economic analysis, and optimization of the best prime mover for the residential scale combined cooling, heating, and power generation system (CCHP). Different prime movers consisting of solid oxide fuel cell (SOFC), internal combustion engine (ICE), microgas turbine (MGT), and hybrid SOFC/GT system for power production are integrated with HRSG and double effect Li/Br refrigeration system for heating and cooling generation, respectively. A parametric study is conducted on the best case to find the key decision variables. Also, a very cutting-edge optimization, which is 3D multi-objective optimization, is carried out for minimizing the unit product cost and emission and maximizing the exergetic efficiency. Results revealed that the hybrid SOFC/GT has higher exergy efficiency of 69.06% and unit product cost of 37.78 $ GJ−1, among other case studies. Also, optimization results indicate a maximum exergy efficiency of 73.15%, and a minimum cost of 25.08 ($ GJ−1) can be reached for the SOFC-/GT-based CCHP system. Moreover, the optimized emission for the best-case scenario becomes 62.52 g MWh−1. Keywords Evolutionary-based optimization · Environmental analysis · Prime mover selection · Solid oxide fuel cell · Stirling engine List of symbols A Area, m2 c Specific exergy cost, $ GJ−1 Ċ Cost rate, $ h−1 Ė Exergy rate, kW f Exergoeconomic factor F Faraday constant, C mol−1 Δ̄g0 Change in molar Gibbs free energy, J/mol h Enthalpy ir Interest rate j Current density, A m−2 J PEME current density * Pedram Hanafizadeh [email protected] * Pouria Ahmadi [email protected] 1
Centre of Excellence in Design and Optimization, School of Mechanical Engineering, University of Tehran, Tehran, Iran
Department of Energy, Polytechnic University of Milan, Milan, Italy
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K Equilibrium constant LHVf Fuel lower heating value M Molar mass ṁf Fuel mass flow rate N Operating hours, h n1 , n2 , … , n7 Mole number of reaction components ne Number of electrons produced per hydrogen mole ṅ Molar flow rate NC Number of cells in the stack P Pressure PR Pressure ratio pH2 O Partial pressure of H2O pH2 Partial pressure of H2 pO2 Partial pressure of O2 Q̇ high Heat rate of the heater inside the Stirling engine, kW Q̇ loss Heat loss rate of cooler inside the Stirling engine, kW R Total ohmic resistance RAR Anode recycling ratio RCR Cathode recycling ratio
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Vol.:(0123456789)
R̄ Universal gas constant, J mol-1 K RV Piston compression ratio of Stirling engine s Specific entropy T Te
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