Investigation of Maximum Power Point Tracking for Thermoelectric Generators

Phillip, Navneesh; Maganga, Othman; Burnham, Keith J.; Ellis, Mark A.; Robinson, Simon; Dunn, Julian; Rouaud, Cédric

doi:10.1007/s11664-012-2460-4

Cited by 29 publications

(6 citation statements)

References 16 publications

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“…Data from the TEG modeling effort at BSU were used as input to the MATLAB® DC-DC controller model with embedded MPPT models. For the P&O MPPT algorithm a MATLAB® built-in model was utilized, and for the ESC MPPT algorithm the approach presented in Philip et al (2013) was implemented.…”

Section: Implementation Of Maximum Peak Power Tracking Algorithms Andmentioning

confidence: 99%

“…Numerical analysis of the MPP with ESC is summarized here for the case of a sine wave perturbation. This analysis is adapted from Philip et al (2013). The nonlinear static map of a TEG is presented as A1where is the duty cycle of the PWM controller and is the value of the unknown optimal duty cycle.…”

Section: Appendix a Numerical Analysis Of Maximum Peak Power With Extmentioning

confidence: 99%

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Integration of Thermoelectric Generator and Wireless Sensor Node Simulators

Agarwal

Zhang

2016

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under the Nuclear Energy Enabling Technologies Program's Advanced Sensors and Instrumentation Pathway aims to develop efficient and reliable thermoelectric generators (TEGs) for self-powered wireless sensor nodes (WSNs) for nuclear applications. The power harvesting technology has crosscutting significance to all U.S. Department of Energy Office of Nuclear Energy research and development programs, because the technology will enable self-powered WSNs in multiple nuclear reactor designs and spent fuel storage facilities using thermal energy available in a nuclear power plant or spent fuel storage facility. This project will address the technology gap that exists in realizing truly wireless sensor nodes due to the need for cables to connect to external power supplies and develop thermoelectric (TE) power harvesting devices to deliver sufficient power to drive the WSNs. The outcomes of the project will lead to significant advancement in sensors and instrumentation technology, reducing cost, improving monitoring reliability, and therefore enhancing safety. The self-powered WSNs could support the long-term safe and economical operation of all reactor designs and fuel cycle concepts, as well as spent fuel storage and many other nuclear science and engineering applications. Most wireless sensor network (comprising thousands of WSNs) applications require operation over extended periods of time beginning with their deployment. Network lifetime is extremely critical for most applications and is one of the limiting factors for energy-constrained networks. Based on the application, there are a wide range of different energy sources suitable for powering WSNs. A battery is traditionally used to power WSNs. The deployed WSN is required to last for a long time. Due to the finite amount of energy present in batteries, it is not feasible to replace batteries. Recently there has been a new surge in the area of energy harvesting where ambient energy in the environment can be utilized to prolong the lifetime of WSNs. Some of the sources of ambient energies are solar power, thermal gradient, human motion and body heat, vibrations, and ambient radio frequency energy. This report focuses on integrating TEG and WSN simulators with a directcurrent-to-direct-current (DC-DC) converter as an interface. A DC-DC converter is essential to balance a wide range of analog, digital, and radio loads acting on the energy source. Also, the voltage level generated by TEGs under varying temperature conditions could be low, irregular, and insufficient to operate a WSN; therefore, DC-DC is required to boost the voltage to a desired level. Most of the main problems with DC-DC converters used in a TEG system are related to impedance matching between the internal resistance of the TEG and the input resistance of the DC-DC converter. This report addresses the issue associated with dynamic impedance matching under varying temperature conditions in the effort to integrate TEGs and WSNs. In this effort, dynamic impedance matching algorithms like perturb and obse...

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Section: Implementation Of Maximum Peak Power Tracking Algorithms Andmentioning

confidence: 99%

Section: Appendix a Numerical Analysis Of Maximum Peak Power With Extmentioning

confidence: 99%

Integration of Thermoelectric Generator and Wireless Sensor Node Simulators

Agarwal

Zhang

2016

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“…Recent researches in thermoelectric generator have introduced the concept of maximum power point tracking technique (MPPT). Phillip et al [12] investigated the impact of maximum power point tracking technique in a thermoelectric generator and found that MPPT technique can increase the power output of the thermoelectric generator. Vadstrup et al [13] applied MPPT technique in an individual thermoelectric module and to a stack of thermoelectric power generators and concluded that if the temperature difference between the thermoelectric generator modules is unequal then the MPPT at module level will give high power output than at stack level.…”

Section: Nomenclaturesmentioning

confidence: 99%

Thermodynamic studies and maximum power point tracking in thermoelectric generator–thermoelectric cooler combined system

Manikandan

Kaushik

2015

Cryogenics

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“…Diğer bir çalışmada, TEJ'ler için K&G algoritması ve uç kontrol arayışı MGNİ algoritmalarının karşılaştırmasını MATLAB/Simulink yazılımıyla Phillip ve diğ. [22] gerçekleştirmişlerdir. Bunun sonucunda uç kontrol arayışı algoritması ile daha hızlı tepki almışlardır.…”

Section: Introductionunclassified

Simulation of maximum power point tracking with buck-boost convertor for thermoelectric generators

Mamur¹,

Çoban²

2020

Pamukkale J Eng Sci

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Enerji çevrim verimliliği %10'lara kadar çıkabilen endüstriyel Termoelektrik Jeneratörler (TEJ) atık ısılardan elektrik enerjisi elde ediniminde kullanılarak enerji verimliliğine katkıda bulunurlar. TEJ iç direnci ile yük direncinin eşit olmaması verim değerini oldukça düşürür. İç direnç ile yük direnci arasındaki dengesizliğin ortadan kaldırılması veya en aza indirilmesi için Maksimum Güç Noktası İzleyici (MGNİ) algoritmaları kullanılır. Bu çalışmada, iç direnç ile yük direnci arasındaki eşitliği sağlamak için Karıştır ve Gözlemle (K&G) metodu temelinde MGNİ algoritması, alçaltan-yükselten çevirici kullanılarak MATLAB/Simulink ile modellenmiştir. İlk olarak, Seebeck sabitine ve sıcaklık farkına bağlı olarak bir TEJ modellemesi yapılmıştır. Bu modellemede, seri ve paralel bağlanacak TEJ'ler belirlendikten sonra, TEJ modelinin çıkışına doğrudan değişken yük direnci bağlanmıştır. Yük direnci ve sıcaklık farkı değişim değerleri için çıkış gücü hesaplanmıştır. Bu durumda, MGNİ'siz TEJ'in yük değişimlerinden oldukça etkilendiği tespit edilmiştir. Verim değeri de buna bağlı olarak sürekli salınımlar yapmıştır. Daha sonra, bu sıcaklık farkı değişimi ve değişken yük K&G MGNİ'li alçaltan-yükselten çevirici sistemine uygulanmıştır. Geliştirilen K&G MGNİ algoritmalı TEJ'in yük ve sıcaklık değişimlerine rağmen Maksimum Güç Noktasını (MGN) %98.72 bir doğrulukla izlediği görülmüş ve TEJ en yüksek verimlilikle her koşulda çalıştırılmıştır. Geliştirilen bu K&G MGNİ algoritması ile kontrol edilen, alçaltanyükselten çeviricili bir TEJ sisteminin modeli sayesinde tasarımcılar için yalnızca Seebeck sabitinin ve seri-paralel bağlı TEJ sayılarının girilmesinin yeterli olacağı bir benzetim çalışması sunulmuştur. Industrial Thermoelectric Generators (TEGs) with up to 10% energy conversion efficiency contribute to energy efficiency by using electrical energy to obtain heat from waste heat. The TEG internal resistance and the unequal load resistance considerably reduce the efficiency. Maximum Power Point Tracking (MPPT) algorithms are used to eliminate or minimize the imbalance between internal resistance and load resistance. In this study, the MPPT algorithm was modeled with MATLAB/Simulink by using the buck-boost converter to ensure the matching between internal resistance and load resistance based on Perturb and Observe (P&O). First, a TEG modeling was performed based on the Seebeck constant and temperature difference. In this modeling, after determining the TEGs to be connected in series and parallel, the variable load resistance was directly connected to the output of the TEG model. The output power of the TEG is calculated for the load resistance and the temperature difference values. In this case, it was determined that TEG without MPPT was highly affected by the load changes. The efficiency value is therefore continuously oscillating. Subsequently, this temperature difference change and the variable load were applied to the TEG system buck-boost converter with P&O MPPT. The TEG system with P&O MPPT algorithm was observed to track ...

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Investigation of Maximum Power Point Tracking for Thermoelectric Generators

Cited by 29 publications

References 16 publications

Integration of Thermoelectric Generator and Wireless Sensor Node Simulators

Integration of Thermoelectric Generator and Wireless Sensor Node Simulators

Thermodynamic studies and maximum power point tracking in thermoelectric generator–thermoelectric cooler combined system

Simulation of maximum power point tracking with buck-boost convertor for thermoelectric generators

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