Multi-objective optimization of concentrated Photovoltaic-Thermoelectric hybrid system via non-dominated sorting genetic algorithm (NSGA II)

Yusuf, Aminu; Bayhan, Nevra; Tiryaki, Hasan; Hamawandi, Bejan; Toprak, Muhammet S.; Ballıkaya, Sedat

doi:10.1016/j.enconman.2021.114065

Cited by 68 publications

(18 citation statements)

References 35 publications

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“…As TE materials can be used for power generation, they can also be used for cooling or thermal management. TE devices have attracted significant interest because of their potential applications in energy harvesting, waste heat recovery in industries and transportation systems, chip cooling, solar cells, temperature sensing, military and space exploration [ 3 , 4 , 5 , 6 , 7 ]. Conventional TE devices are made of compact solid-state materials without any moving parts, which gives them a high operational reliability and makes them scalable [ 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

Minute-Made, High-Efficiency Nanostructured Bi2Te3 via High-Throughput Green Solution Chemical Synthesis

et al. 2021

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Scalable synthetic strategies for high-quality and reproducible thermoelectric (TE) materials is an essential step for advancing the TE technology. We present here very rapid and effective methods for the synthesis of nanostructured bismuth telluride materials with promising TE performance. The methodology is based on an effective volume heating using microwaves, leading to highly crystalline nanostructured powders, in a reaction duration of two minutes. As the solvents, we demonstrate that water with a high dielectric constant is as good a solvent as ethylene glycol (EG) for the synthetic process, providing a greener reaction media. Crystal structure, crystallinity, morphology, microstructure and surface chemistry of these materials were evaluated using XRD, SEM/TEM, XPS and zeta potential characterization techniques. Nanostructured particles with hexagonal platelet morphology were observed in both systems. Surfaces show various degrees of oxidation, and signatures of the precursors used. Thermoelectric transport properties were evaluated using electrical conductivity, Seebeck coefficient and thermal conductivity measurements to estimate the TE figure-of-merit, ZT. Low thermal conductivity values were obtained, mainly due to the increased density of boundaries via materials nanostructuring. The estimated ZT values of 0.8–0.9 was reached in the 300–375 K temperature range for the hydrothermally synthesized sample, while 0.9–1 was reached in the 425–525 K temperature range for the polyol (EG) sample. Considering the energy and time efficiency of the synthetic processes developed in this work, these are rather promising ZT values paving the way for a wider impact of these strategic materials with a minimum environmental impact.

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Section: Introductionmentioning

confidence: 99%

Minute-Made, High-Efficiency Nanostructured Bi2Te3 via High-Throughput Green Solution Chemical Synthesis

et al. 2021

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“…Abedinnezhad et al [ 85 ] carried out MOO of irreversible Dual-Miller cycle with

, ecological coefficient of performance and

as OFs. Yusuf et al [ 86 ] used NSGA-II to optimize some parameters of the centralized photovoltaic thermoelectric hybrid system. Based on NSGA II, Xiao et al [ 87 ] proposed a steam power system design and optimization strategy considering pollutant emission reduction technology to obtain the balance between environmental and economic objectives.…”

Section: Introductionmentioning

confidence: 99%

Four-Objective Optimization of an Irreversible Magnetohydrodynamic Cycle

Chen

et al. 2022

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Based on the existing model of an irreversible magnetohydrodynamic cycle, this paper uses finite time thermodynamic theory and multi-objective genetic algorithm (NSGA-II), introduces heat exchanger thermal conductance distribution and isentropic temperature ratio of working fluid as optimization variables, and takes power output, efficiency, ecological function, and power density as objective functions to carry out multi-objective optimization with different objective function combinations, and contrast optimization results with three decision-making approaches of LINMAP, TOPSIS, and Shannon Entropy. The results indicate that in the condition of constant gas velocity, deviation indexes are 0.1764 acquired by LINMAP and TOPSIS approaches when four-objective optimization is performed, which is less than that (0.1940) of the Shannon Entropy approach and those (0.3560, 0.7693, 0.2599, 0.1940) for four single-objective optimizations of maximum power output, efficiency, ecological function, and power density, respectively. In the condition of constant Mach number, deviation indexes are 0.1767 acquired by LINMAP and TOPSIS when four-objective optimization is performed, which is less than that (0.1950) of the Shannon Entropy approach and those (0.3600, 0.7630, 0.2637, 0.1949) for four single-objective optimizations, respectively. This indicates that the multi-objective optimization result is preferable to any single-objective optimization result.

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“…On the basis of references [ 67 , 68 ], this study will analyze the effects of mechanical losses, as well as heat leakage, regeneration loss, and thermal resistance on SHE cycles with linear phenomenological HTL (

). The temperature ratio (

) of the WF and volume compression ratio (

) of the cycle will be selected as optimization variables, then the NSGA-II algorithm [ 79 , 80 , 81 , 82 ] will be applied to perform MOO on four OOs, that is,

, and dimensionless PD (

). The Pareto optimal solution of four-, three-, two-, and single-objective optimizations will be reached, and the optimal scheme will be reached by selecting the minimum deviation indexes (

) [ 83 ] with TOPSIS [ 84 , 85 , 86 ], LINMAP [ 87 , 88 ], and Shannon Entropy [ 89 , 90 ] decision-making strategies.…”

Section: Introductionmentioning

confidence: 99%

Four-Objective Optimization of an Irreversible Stirling Heat Engine with Linear Phenomenological Heat-Transfer Law

Chen

et al. 2022

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This paper combines the mechanical efficiency theory and finite time thermodynamic theory to perform optimization on an irreversible Stirling heat-engine cycle, in which heat transfer between working fluid and heat reservoir obeys linear phenomenological heat-transfer law. There are mechanical losses, as well as heat leakage, thermal resistance, and regeneration loss. We treated temperature ratio x of working fluid and volume compression ratio λ as optimization variables, and used the NSGA-II algorithm to carry out multi-objective optimization on four optimization objectives, namely, dimensionless shaft power output P¯s, braking thermal efficiency ηs, dimensionless efficient power E¯p and dimensionless power density P¯d. The optimal solutions of four-, three-, two-, and single-objective optimizations are reached by selecting the minimum deviation indexes D with the three decision-making strategies, namely, TOPSIS, LINMAP, and Shannon Entropy. The optimization results show that the D reached by TOPSIS and LINMAP strategies are both 0.1683 and better than the Shannon Entropy strategy for four-objective optimization, while the Ds reached for single-objective optimizations at maximum P¯s, ηs, E¯p, and P¯d conditions are 0.1978, 0.8624, 0.3319, and 0.3032, which are all bigger than 0.1683. This indicates that multi-objective optimization results are better when choosing appropriate decision-making strategies.

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Multi-objective optimization of concentrated Photovoltaic-Thermoelectric hybrid system via non-dominated sorting genetic algorithm (NSGA II)

Cited by 68 publications

References 35 publications

Minute-Made, High-Efficiency Nanostructured Bi2Te3 via High-Throughput Green Solution Chemical Synthesis

Minute-Made, High-Efficiency Nanostructured Bi2Te3 via High-Throughput Green Solution Chemical Synthesis

Four-Objective Optimization of an Irreversible Magnetohydrodynamic Cycle

Four-Objective Optimization of an Irreversible Stirling Heat Engine with Linear Phenomenological Heat-Transfer Law

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