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Energies 2017, 10(11), 1703; doi:10.3390/en10111703

Metaheuristic Techniques in Enhancing the Efficiency and Performance of Thermo-Electric Cooling Devices

1
Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
2
Department of Fundamental and Applied Sciences, Universiti Teknologi Petronas, Seri Iskandar, Perak 32610, Malaysia
3
Department of Computer Engineering, Suleyman Demirel University, Isparta 32260, Turkey
4
Department of Computer & Information System, Universiti Teknologi Petronas, Seri Iskandar, Perak 32610, Malaysia
*
Author to whom correspondence should be addressed.
Received: 11 August 2017 / Revised: 23 August 2017 / Accepted: 2 September 2017 / Published: 25 October 2017
(This article belongs to the Section Energy Sources)

Abstract

The objective of this paper is to focus on the technical issues of single-stage thermo-electric coolers (TECs) and two-stage TECs and then apply new methods in optimizing the dimensions of TECs. In detail, some metaheuristics—simulated annealing (SA) and differential evolution (DE)—are applied to search the optimal design parameters of both types of TEC, which yielded cooling rates and coefficients of performance (COPs) individually and simultaneously. The optimization findings obtained by using SA and DE are validated by applying them in some defined test cases taking into consideration non-linear inequality and non-linear equality constraint conditions. The performance of SA and DE are verified after comparing the findings with the ones obtained applying the genetic algorithm (GA) and hybridization technique (HSAGA and HSADE). Mathematical modelling and parameter setting of TEC is combined with SA and DE to find better optimal findings. The work revealed that SA and DE can be applied successfully to solve single-objective and multi-objective TEC optimization problems. In terms of stability, reliability, robustness and computational efficiency, they provide better performance than GA. Multi-objective optimizations considering both objective functions are useful for the designer to find the suitable design parameters of TECs which balance the important roles of cooling rate and COP. View Full-Text
Keywords: metaheuristic techniques; optimization; optimization algorithms; single-objective optimization; multi-objective optimization; artificial intelligence; thermos-electric cooling devices metaheuristic techniques; optimization; optimization algorithms; single-objective optimization; multi-objective optimization; artificial intelligence; thermos-electric cooling devices
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Vasant, P.; Kose, U.; Watada, J. Metaheuristic Techniques in Enhancing the Efficiency and Performance of Thermo-Electric Cooling Devices. Energies 2017, 10, 1703.

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