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Inverse dynamic analysis type of MPPT control strategy in a thermoelectric-solar hybrid energy harvesting system

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  • M. Yusop, A.
  • Mohamed, R.
  • Mohamed, A.

Abstract

This study presents the development of a novel inverse dynamic analysis-maximum power point tracking (IDA-MPPT) scheme in a hybrid energy harvesting system between thermoelectric module (TEM) and solar array (SA). The proposed method initially changes the harvested voltage response from both sources to be the third-order exponential function. This input function selection is based on the capability of this function to stabilize the initial response system and maintain its final position despite a prolonged response time. The mV voltage value from TEM is easily boosted up to nearly 5 V using this method. With this hybridization, the total obtained voltage is doubled to become 9.7 V, which results in a total power of 0.722 W. Furthermore, the method also allows for a fast tracking system, which enables faster voltage boosting and supercapacitor charging. The supercapacitor only requires less than 5 min to complete charging and boost the voltage to almost 5 V. Thus, a satisfactory value is obtained as compared with that of the TEM system with a chosen MPPC board.

Suggested Citation

  • M. Yusop, A. & Mohamed, R. & Mohamed, A., 2016. "Inverse dynamic analysis type of MPPT control strategy in a thermoelectric-solar hybrid energy harvesting system," Renewable Energy, Elsevier, vol. 86(C), pages 682-692.
  • Handle: RePEc:eee:renene:v:86:y:2016:i:c:p:682-692
    DOI: 10.1016/j.renene.2015.08.071
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    References listed on IDEAS

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    1. Daraban, Stefan & Petreus, Dorin & Morel, Cristina, 2014. "A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading," Energy, Elsevier, vol. 74(C), pages 374-388.
    2. Belmokhtar, K. & Doumbia, M.L. & Agbossou, K., 2014. "Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator)," Energy, Elsevier, vol. 76(C), pages 679-693.
    3. Mäki, Anssi & Valkealahti, Seppo, 2014. "Differentiation of multiple maximum power points of partially shaded photovoltaic power generators," Renewable Energy, Elsevier, vol. 71(C), pages 89-99.
    4. Sundareswaran, K. & Vignesh kumar, V. & Palani, S., 2015. "Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions," Renewable Energy, Elsevier, vol. 75(C), pages 308-317.
    5. Qi, Jun & Zhang, Youbing & Chen, Yi, 2014. "Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions," Renewable Energy, Elsevier, vol. 66(C), pages 337-345.
    6. Kossyvakis, D.N. & Vossou, C.G. & Provatidis, C.G. & Hristoforou, E.V., 2015. "Computational and experimental analysis of a commercially available Seebeck module," Renewable Energy, Elsevier, vol. 74(C), pages 1-10.
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    1. Hao, Daning & Qi, Lingfei & Tairab, Alaeldin M. & Ahmed, Ammar & Azam, Ali & Luo, Dabing & Pan, Yajia & Zhang, Zutao & Yan, Jinyue, 2022. "Solar energy harvesting technologies for PV self-powered applications: A comprehensive review," Renewable Energy, Elsevier, vol. 188(C), pages 678-697.
    2. Ssennoga Twaha & Jie Zhu & Luqman Maraaba & Kuo Huang & Bo Li & Yuying Yan, 2017. "Maximum Power Point Tracking Control of a Thermoelectric Generation System Using the Extremum Seeking Control Method," Energies, MDPI, vol. 10(12), pages 1-18, December.
    3. Liu, Huicong & Fu, Hailing & Sun, Lining & Lee, Chengkuo & Yeatman, Eric M., 2021. "Hybrid energy harvesting technology: From materials, structural design, system integration to applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    4. Zhu, Wei & Deng, Yuan & Wang, Yao & Shen, Shengfei & Gulfam, Raza, 2016. "High-performance photovoltaic-thermoelectric hybrid power generation system with optimized thermal management," Energy, Elsevier, vol. 100(C), pages 91-101.

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