Comparative Study of Maximum Power Point Tracking Algorithms for Thermoelectric Generator

  • Abdelkader BelboulaEmail author
  • Rachid Taleb
  • Ghalem Bachir
  • Fayçal Chabni
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)


Variations in load and temperature can cause a thermoelectric generator (TEG) to operate at a voltage that does not produce the maximum possible power for a given temperature difference. Therefore a maximum power point tracker (MPPT) is used to force the generator to a voltage that produces maximum power. This paper presents a comparative simulation study of two important MPPT algorithms specifically perturb and observe and incremental conductance. The Matlab Simulink environment is used to analyze and interpret the simulation results of these algorithms, and therefore show the performance and limitations of each algorithm. As a result, the Incremental conductance method has shown promise as a suitable MPPT algorithm for a TEG subjected to steady state conditions.


Maximum power point tracking Thermoelectric generator TEG INC MPPT P&O MPPT 


  1. 1.
    Willis, H.L., Scott, W.G.: Distributed Power Generation—Planning and Evaluation, 1st edn. Marcel Dekker, New York (2000). ISBN 0-8247-0336-7CrossRefGoogle Scholar
  2. 2.
    Rahman, S.: Going green: the growth of renewable energy. IEEE Power Energy Mag. 1(6), 16–18 (2003)CrossRefGoogle Scholar
  3. 3.
    Rowe, D.: Thermoelectric waste heat recovery as a renewable energy source. Int. J. Innov. Energy Syst. Power 1, 13–23 (2006)Google Scholar
  4. 4.
    Dalala, Z.M., Zahid, Z.U.: New MPPT algorithm based on indirect open circuit voltage and short circuit current detection for thermoelectric generators. In: Energy Conversion Congress and Exposition (ECCE), 2015 IEEE, pp. 1062–1067 (2015)Google Scholar
  5. 5.
    Riffat, S.B., Ma, X.: Thermoelectrics: a review of present and potential applications. Appl. Therm. Eng. 23, 913–935 (2003)CrossRefGoogle Scholar
  6. 6.
    Rowe, D.: Thermoelectrics, an environmentally-friendly source of electrical power. Renew. Energy 16, 1251–1256 (1999)CrossRefGoogle Scholar
  7. 7.
    Phillip, N., Maganga, O., Burnham, K.J., Dunn, J., Rouaud, C., Ellis, M.A., Robinson, S.: Modelling and simulation of a thermoelectric generator for waste heat energy recovery in Low Carbon Vehicles. In: 2012 2nd International Symposium on Environment. Friendly Energies and Applications (EFEA), pp. 94–99 (2012)Google Scholar
  8. 8.
    Hendricks, T., Choate, W.T.: Engineering Scoping Study of Thermoelectric Generator Systems for Industrial Waste Heat Recovery. Pacifc Northwest National Laboratory, Richland (2006)CrossRefGoogle Scholar
  9. 9.
    Fernandes, A.E.S.S.: Conversão de energia com células de Peltier. Dissertação (Mestrado). Universidade Nova de Lisboa, Lisboa (2012)Google Scholar
  10. 10.
    Kasa, N., Iida, T., Liang, C.: Flyback inverter controlled by sensorless current MPPT for photovoltaic power system. IEEE Trans. Ind. Electron. 52, 1145–1152 (2005)CrossRefGoogle Scholar
  11. 11.
    Rae-young, K., Jih-Sheng, L.: A seamless mode transfer maximum power point tracking controller for thermoelectric generator applications. IEEE Trans. Power Electron. 23, 2310–2318 (2008)CrossRefGoogle Scholar
  12. 12.
    Esram, T., Chapman, P.L.: Comparison of photovoltaic array maximum power point tracking methods. IEEE Trans. Energy Convers. 22(2), 439–449 (2007)CrossRefGoogle Scholar
  13. 13.
    Dolara, A., Faranda, R., Leva, S.: Energy comparison of seven MPPT techniques for PV systems. J. Electromagn. Anal. Appl. 3, 152–162 (2009)Google Scholar
  14. 14.
    Pikutis, M., Vasarevicius, D., Martavicius, R.: Maximum power point tracking in solar power plants under partially shaded condition. Elektronika ir Elektrotechnika 20(4), 49–52 (2014)CrossRefGoogle Scholar
  15. 15.
    Lineykin, S., Ben-yaakov, S.: Modeling and analysis of thermoelectric modules. IEEE Trans. Ind. Appl. 43(2), 505–512 (2007)CrossRefGoogle Scholar
  16. 16.
    Josephine, R.L., Padmabeaula, A., Raj, A.D.: Simulation of incremental conductance mppt with direct control and fuzzy logic methods using SEPIC converter. J. Electr. Eng. 13(3), 91–99 (2013)Google Scholar
  17. 17.
    Femia, F., Petrone, G., Spagnuolo, G., Vitelli, M.: Power Electronics and Control Techniques for Maximum Energy Harvesting in Photovoltaic Systems, pp. 35–84. CRC Press, Boca Raton (2013)Google Scholar
  18. 18.
    Piegari, L., Rizzo, R.: Adaptive perturb and observe algorithm for photovoltaic maximum power point tracking. IET Renew. Power Gener. 4, 317–328 (2010)CrossRefGoogle Scholar
  19. 19.
    Liu, F., Kang, Y., Zhang, Y., Duan, S.: Comparison of P&O and hill climbing MPPT methods for grid-connected PV generator. In: 3rd IEEE Conference on Industrial Electronics and Applications” 3–5 June 2008; Singapore. IEEE, New York, pp 804–807Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Abdelkader Belboula
    • 1
    Email author
  • Rachid Taleb
    • 2
  • Ghalem Bachir
    • 1
  • Fayçal Chabni
    • 2
  1. 1.LDEE Laboratory, Electrical Engineering DepartmentUSTO-MB UniversityOranAlgeria
  2. 2.LGEER Laboratory, Electrical Engineering DepartmentHassiba Benbouali UniversityChlefAlgeria

Personalised recommendations