2022
DOI: 10.1016/j.ijhydene.2022.04.066
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Systematic analysis and multi-objective optimization of an integrated power and freshwater production cycle

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Cited by 11 publications
(5 citation statements)
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“…87 This analysis is based on fundamental thermodynamic principles, namely energy conservation and mass conservation. 88,89 Generally assuming a steady-flow, steady-state process, according to Equation (1), mass and energy balance are applied to calculate the useful energy and efficiencies. The mass balance can be defined in the rating form as follow 90 :…”
Section: Energy Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…87 This analysis is based on fundamental thermodynamic principles, namely energy conservation and mass conservation. 88,89 Generally assuming a steady-flow, steady-state process, according to Equation (1), mass and energy balance are applied to calculate the useful energy and efficiencies. The mass balance can be defined in the rating form as follow 90 :…”
Section: Energy Analysismentioning
confidence: 99%
“…It can give information on the quantity of energy input and output of a system 87 . This analysis is based on fundamental thermodynamic principles, namely energy conservation and mass conservation 88,89 …”
Section: Mathematical Modelingmentioning
confidence: 99%
“…In a general and simplified manner, mass and energy rate balances can be written as 40,43,44 : intrueṁ=outtrueṁ, $\sum _{\mathrm{in}}\dot{m}=\sum _{\mathrm{out}}\dot{m},$ trueQ̇trueẆ=Ptrueṁ(hf+(hh0))Rtrueṁ(hf+(hh0)). $\dot{Q}-\dot{W}=\sum _{P}\dot{m}({h}_{f}+(h-{h}_{0}))-\sum _{R}\dot{m}({h}_{f}+(h-{h}_{0})).$Here, Q̇ and Ẇ denote the heat transfer rate and work rate respectively, ṁ is the mass flow rate, and h is the specific enthalpy. Subscripts P , f , R , and 0 denote products, formation, reactants, and dead state conditions, respectively.…”
Section: Mathematical Modelingmentioning
confidence: 99%
“…Utilizing genetic algorithms for multi-objective optimization is an effective approach to find the best solutions when dealing with objectives that are in conflict [15]. Abdullah et al [16] introduced a poly-generation plant for CCHP and freshwater generation and used multiobjective optimization to improve its energy and exergy efficiency from 73.9% to 79% and 71.35% to 73.9%, respectively, and reduce its total cost from 10.62 USD/h to 9.26 USD/h.…”
Section: Introductionmentioning
confidence: 99%