Modeling and genetic algorithm-based multi-objective optimization of the MED-TVC desalination system

Esfahani, Iman Janghorban; Ataei, Abtin; Kodialbail, Vidya Shetty; Oh, TaeSuk; Park, Jae Hyung; Yoo, ChangKyoo

doi:10.1016/j.desal.2012.02.012

Cited by 96 publications

(17 citation statements)

References 38 publications

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“…Analysis by Esfahani et al [45] and Eshoul et al [46] confirmed that a higher number of effects in the MED process may result in higher gained output ratio and lower product exergy costs. Attributing to irreversibilities in thermo-compressor and evaporators, a study on a 4-stage 46,000 m 3 /day capacity plant reported an exergy efficiency of 3.95% [45]. Using specialized software, a comprehensive study on a 24,000 m 3 /day capacity plant has shown that 40% and 35% exergy destruction have occurred in thermos-compressor and MED evaporator effects, respectively [46].…”

Section: Med-tvc Processmentioning

confidence: 96%

“…A detailed first and second law analysis of the MED-TVC process showed that the process is insensitive to concentration factor, rather a higher value of compression ratio should be maintained in the compressor for reduction of exergy destruction [44]. Analysis by Esfahani et al [45] and Eshoul et al [46] confirmed that a higher number of effects in the MED process may result in higher gained output ratio and lower product exergy costs. Attributing to irreversibilities in thermo-compressor and evaporators, a study on a 4-stage 46,000 m 3 /day capacity plant reported an exergy efficiency of 3.95% [45].…”

Section: Med-tvc Processmentioning

confidence: 96%

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Exergy Evaluation of Desalination Processes

Gude

2018

ChemEngineering

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Desalination of sea or brackish water sources to provide clean water supplies has now become a feasible option around the world. Escalating global populations have caused the surge of desalination applications. Desalination processes are energy intensive which results in a significant energy portfolio and associated environmental pollution for many communities. Both electrical and heat energy required for desalination processes have been reduced significantly over the recent years. However, the energy demands are still high and are expected to grow sharply with increasing population. Desalination technologies utilize various forms of energy to produce freshwater. While the process efficiency can be reported by the first law of thermodynamic analysis, this is not a true measure of the process performance as it does not account for all losses of energy. Accordingly, the second law of thermodynamics has been more useful to evaluate the performance of desalination systems. The second law of thermodynamics (exergy analysis) accounts for the available forms of energy in the process streams and energy sources with a reference environment and identifies the major losses of exergy destruction. This aids in developing efficient desalination processes by eliminating the hidden losses. This paper elaborates on exergy analysis of desalination processes to evaluate the thermodynamic efficiency of major components and process streams and identifies suitable operating conditions to minimize exergy destruction. Well-established MSF, MED, MED-TVC, RO, solar distillation, and membrane distillation technologies were discussed with case studies to illustrate the exergy performances.

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Section: Med-tvc Processmentioning

confidence: 96%

Section: Med-tvc Processmentioning

confidence: 96%

Exergy Evaluation of Desalination Processes

Gude

2018

ChemEngineering

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“…The enactment of single stage pilot scale RO plant is quite complex to the quality of the feed water and plant operating conditions ( Janghorban Esfahani et al 2012). Most perfect membrane transport equations of steady-state in the form of distributed parameters can be derivedbased on solution-diffusion model and film theory.…”

Section: Mathematical Modeling Of Single Stage Pilot Scale Ro Processmentioning

confidence: 99%

Design, implementation, control and optimization of single stage pilot scale reverse osmosis process

Guna¹,

Prabhakaran²,

Thirumarimurugan³

2021

Water Science and Technology

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In this paper, a single-stage pilot-scale RO (Reverse Osmosis) process is considered. The process is mainly used in various chemical industries such as dye, pharmaceutical, Beverage, and so on. Initially, mathematical modeling of the process is to be done followed by linearization of the system. Here a dual loop construction with a master and a slave is used. The slave uses the conventional PID (Proportional Integral Derivative) with a reference model of the RO process and the master uses the FOPID (Fractional Order Proportional Integral Derivative) with a real time RO process. The slave's output is compared with output of the real time RO process to obtain the error which is in turn used to tune the master. The slave controller is tuned using Ziegler Nicholas method and the error criterion such as IAE (Integral Absolute Error), ISE (Integral Squared Error), ITSE (Integral Time Squared Error), ITAE (Integral Time Absolute Error) are calculated and the minimum among them was chosen as the objective function for the master loop tuning. Hence the tuning of the controller becomes a whole. Therefore two optimization techniques such as PSO (Particle Swarm Optimization) and Bacterial Foraging Optimization Algorithm (BFO) are used for the tuning of the master loop. From the calculations the ITSE was having the minimum value among the performance indices hence it was used as the objective function for the BFO and PSO. The best-tuned values will be obtained with the use of these techniques and the best among all can be considered for various industrial applications. Finally, the performance of the process is compared with both techniques and BFO outperforms the PSO from the simulations.

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“…An economic model was developed to evaluate the economic performance of the optimal retrofitted system. The model was developed using a multi-integer linear program to obtain the total annual cost (TAC) of the system [40]. The overall TAC is a summation of the subsystems' TAC including PVs, WTs, and battery banks (BB) considering a constant TAC for the MBR as given in Equation 22.…”

Section: Economic Modelmentioning

confidence: 99%

Optimal Management of a Hybrid Renewable Energy System Coupled with a Membrane Bioreactor Using Enviro-Economic and Power Pinch Analyses for Sustainable Climate Change Adaption

et al. 2018

Self Cite

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This study proposed an optimal hybrid renewable energy system (HRES) to sustainably meet the dynamic electricity demand of a membrane bioreactor. The model-based HRES consists of solar photovoltaic panels, wind turbines, and battery banks with grid connectivity. Three scenarios, 101 sub-scenarios, and three management cases were defined to optimally design the system using a novel dual-scale optimization approach. At the system scale, the power-pinch analysis was applied to minimize both the size of components and the outsourced needed electricity (NE) from Vietnam’s electrical grid. At a local-scale, economic and environmental models were integrated, and the system was graphically optimized using a novel objective function, combined enviro-economic costs (CEECs). The results showed that the optimal CEECs were $850,710/year, $1,030,628/year, and $1,693,476/year for the management cases under good, moderate, and unhealthy air qualities, respectively. The smallest CEEC was obtained when 47% of the demand load of the membrane bioreactor was met using the HRES and the rest was supplied by the grid, resulting in 6,800,769 kg/year of CO2 emissions.

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Modeling and genetic algorithm-based multi-objective optimization of the MED-TVC desalination system

Cited by 96 publications

References 38 publications

Exergy Evaluation of Desalination Processes

Exergy Evaluation of Desalination Processes

Design, implementation, control and optimization of single stage pilot scale reverse osmosis process

Optimal Management of a Hybrid Renewable Energy System Coupled with a Membrane Bioreactor Using Enviro-Economic and Power Pinch Analyses for Sustainable Climate Change Adaption

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