Detailed modeling of a thermoelectric generator for maximum power point tracking

Mamur, Hayati; Çoban, Yusuf

doi:10.3906/elk-1907-166

Cited by 33 publications

(13 citation statements)

References 29 publications

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“…MPT occurred at R load of 1-10 Ω [23] Case study N (Park et al, 2014) Showed the use of a low-cost microcontroller and temperature sensor-based circuit, to track TEG MPP with a 1.1% tracking error [24] Case study O (Yildiz et al, 2013) Compared TEG and solar energy conversion. A TEG generates more power relative to solar module of same size but more costly [27] Case study P (Apertet et al, 2014) Deduced that a TEG output power and efficiency in a thermal environment can be simultaneously maximised if its heat flux is constant but not the case if its temperature difference is constant [25] Case study Q (Ebrahimi and Derakhshan, 2018) Proved that a TEC LT-PEM FC hybrid CCHP system is capable of producing 2.79 kW of electricity, 3.04 kW of heat, and 26.8 W of cooling with a total efficiency of~77% and fuel saving of 43.25% [50] Case study R (Mamur and Çoban, 2020)…”

Section: Resultsmentioning

confidence: 99%

“…The results showed that the cycle is capable of producing 2.79 kW of electricity, 3.04 kW of Figure 16: Influence of thermal environment on optimal working conditions of TEGs (adapted from [27]). [50], the maximum power is attained when the load connected to a TEG matches its internal resistance. However, impedance matching is not always practically guaranteed.…”

Section: Influence Of Thermal Environment On Optimal Workingmentioning

confidence: 99%

“…Simulated and experimental TEG, boost converter, and P&O MPPT schemes (adapted from[50]). 19Journal of Energy…”

mentioning

confidence: 99%

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A Structural Review of Thermoelectricity for Fuel Cell CCHP Applications

2020

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This article starts by introducing the ongoing South Africa electricity crisis followed by thermoelectricity, in which eighteen miscellaneous applicable case studies are structurally analysed in detail. The aim is to establish best practices for the R&D of an efficient thermoelectric (TE) and fuel cell (FC) CCHP system. The examined literature reviews covered studies that focused on the thermoelectricity principle, highlighting TE devices’ basic constructions, TEGs and TECs as well as investigations on the applications of thermoelectricity with FCs, whereby thermoelectricity was applied to recover waste heat from FCs to boost the power generation capability by ~7–10%. Furthermore, nonstationary TEGs whose generated power can be increased by pulsing the DC-DC power converter showed that an output power efficiency of 8.4% is achievable and that thicker TEGs with good area coverage can efficiently harvest waste heat energy in dynamic applications. TEG and TEC exhibit duality and the higher the TEG temperature difference, the more the generated power—which can be stabilised using the MPPT technique with a 1.1% tracking error. A comparison study of TEG and solar energy demonstrated that TEG generates more power compared to solar cells of the same size, though more expensively. TEG output power and efficiency in a thermal environment can be maximised simultaneously if its heat flux is stable but not the case if its temperature difference is stable. The review concluded with a TEC LT-PEM-FC hybrid CCHP system capable of generating 2.79 kW of electricity, 3.04 kW of heat, and 26.8 W of cooling with a total efficiency of ~77% and fuel saving of 43.25%. The presented research is the contribution brought forward, as it heuristically highlights miscellaneous thermoelectricity studies/parameters of interests in a single manuscript, which further established that practical applications of thermoelectricity are possible and can be innovatively applied together with FC for efficient CCHP applications.

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Section: Resultsmentioning

confidence: 99%

Section: Influence Of Thermal Environment On Optimal Workingmentioning

confidence: 99%

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A Structural Review of Thermoelectricity for Fuel Cell CCHP Applications

2020

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“…These multiple maxima are termed local maxima and global maxima [45,46]. Therefore, under NTUD, BMO is required to generate reference voltage for maximizing power/energy output [47][48][49][50].…”

Section: Configuration Of Teg Systemmentioning

confidence: 99%

Optimal Control of Centralized Thermoelectric Generation System under Nonuniform Temperature Distribution Using Barnacles Mating Optimization Algorithm

et al. 2021

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The need for renewable energy resources is ever-increasing due to the concern for environmental issues associated with fossil fuels. Low-cost high-power-density manufacturing techniques for the thermoelectric generators (TEG) have added to the technoeconomic feasibility of the TEG systems as an effective power generation system in heat recovery, cooling, electricity, and engine-efficiency applications. The environment-dependent factors such as the nonuniform distribution of heat, damage to the heat-transfer coating between sinks and sources, and mechanical faults create nonuniform current generation and impedance mismatch causing power loss. As a solution to this nonlinear multisolution problem, an improved MPPT control is presented, which utilizes the improvised barnacle mating optimization (BMO). The case studies are formulated to gauge the performance of the proposed BMP MPPT control under nonuniform temperature distribution. The results are compared to the grey wolf optimization (GWO), particle swarm optimization (PSO), and cuckoo search (CS) algorithm. Faster global maximum power point tracking (GMPP) within 381 ms, higher power tracking efficiency of up to 99.93%, and least oscillation ≈0.8 W are achieved by the proposed BMO with the highest energy harvest on average. The statistical analysis further solidifies the better performance of the proposed controller with the least root mean square error (RMSE), RE, and highest SR.

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“…A multi-stage TEC module in cascade was examined in [8]; whereas in [9], an extensive mathematical analyses were articulated for TEG and TEC design and materials. A TEG model was developed in [10] for maximum power point tracking but lacks the detailed underlining maths and the parallel TEG combinations was limited to just 2. A comprehensive TEG and TEC models with the detailed maths supporting the TEG and TEC models, were presented respectively in [11] and [12].…”

Section: Introductionmentioning

confidence: 99%

Thermoelectric Generators (TEGs) and Thermoelectric Coolers (TECs) Modeling and Optimal Operation Points Investigation

Bayendang¹,

Kahn²,

Balyan³

2022

Adv. sci. technol. eng. syst. j.

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Sustainable energy is gradually becoming the norm today due to greenhouse warming effects; as a result, the quests for different renewable energy sources such as photovoltaic cells as well as energy efficient electrical appliances are becoming popular. Therefore, this article explores the alternative energy case for thermoelectricity with focus on the steadystate mathematics, mixed modelings and simulations of multiple TEGs and TECs modules to study their performance dynamics and to establish their optimal operation points using Matlab and Simulink. The research substantiates that the output current from TEGs or input current to TECs, initially respectively increases the output power of TEGs and the cooling power of TECs, until the current reaches a certain maximum optimal point, after which any further increase in the current, decreases the TEGs' and or TECs' respective output and cooling powers as well as efficiencies, due to Ohmic heating and or entropy change caused by the increasing current. The research main contributions are elaborate easy to understand TEGs/TECs theoretical formulations as well as static and dynamic simulated models in Matlab/Simulink, that can be used initially to dynamically investigate an infinite quantity of TEG and TEC modules connections, be it in series and or in parallel. This is to assist system designers grasp TEGs and TECs theoretical operations better and their limits, when designing energy efficient waste heat recovery (using TEGs)/cooling (using TECs) systems for industrial, residential, commercial and vehicular applications.

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Detailed modeling of a thermoelectric generator for maximum power point tracking

Cited by 33 publications

References 29 publications

A Structural Review of Thermoelectricity for Fuel Cell CCHP Applications

A Structural Review of Thermoelectricity for Fuel Cell CCHP Applications

Optimal Control of Centralized Thermoelectric Generation System under Nonuniform Temperature Distribution Using Barnacles Mating Optimization Algorithm

Thermoelectric Generators (TEGs) and Thermoelectric Coolers (TECs) Modeling and Optimal Operation Points Investigation

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