PV Module Temperature Estimation by Using ANFIS

  • Challa Babu
  • Ponnambalam PathipooranamEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1048)


The recent advantages in the thermal extraction schemes of Photovoltaic (PV) systems became more feasible for domestic applications. The amount of thermal energy available at the PV backside is the source for all thermal extraction/utilizing schemes. But, till now, there is no accurate theoretical method to find the module temperature by any mathematical equation to be adaptable for all the conditions. In this work, we introduced the soft computing based estimation using Adaptive Neural Fuzzy Inference Systems (ANFIS) tool in MATLAB to estimate the module temperature of PV with respect to change of irradiance, ambient temperature, and wind velocity.


PV/thermal systems Temperature estimation ANFIS Error reduction 


  1. 1.
    Babu, C., Ponnambalam, P.: The role of thermoelectric generators in the hybrid PV/T systems: a review. Energy Convers. Manag. 151, 368–385 (2017)CrossRefGoogle Scholar
  2. 2.
    Skoplaki, E.P., Palyvos, J.A.: Operating temperature of photovoltaic modules: a survey of pertinent correlations. Renew. Energy 34, 23–29 (2009)CrossRefGoogle Scholar
  3. 3.
    Skoplaki, E., Palyvos, J.A.: On the temperature dependence of photovoltaic module electrical performance: a review of efficiency/power correlations. Sol. Energy 83, 614–624 (2009)CrossRefGoogle Scholar
  4. 4.
    Skoplaki, E., Boudouvis, A.G., Palyvos, J.A.: A simple correlation for the operating temperature of photovoltaic modules of arbitrary mounting. Sol. Energy Mater. Sol. Cells 92, 1393–1402 (2008)CrossRefGoogle Scholar
  5. 5.
    Muzathik, A.M.: Photovoltaic modules operating temperature estimation using a simple correlation. Int. J. Energy Eng. 4, 151 (2014)Google Scholar
  6. 6.
    Kharb, R.K., Shimi, S.L., Chatterji, S., Ansari, M.F.: Modeling of solar PV module and maximum power point tracking using ANFIS. Renew. Sustain. Energy Rev. 33, 602–612 (2014)CrossRefGoogle Scholar
  7. 7.
    Babu, C., Ponnambalam, P.: The theoretical performance evaluation of hybrid PV-TEG system. Energy Convers. Manag. 173, 450–460 (2018)CrossRefGoogle Scholar
  8. 8.
    Bayrak, F., Abu-Hamdeh, N., Alnefaie, K.A., Öztop, H.F.: A review on exergy analysis of solar electricity production. Renew. Sustain. Energy Rev. 74, 755–770 (2017)CrossRefGoogle Scholar
  9. 9.
    Fudholi, A., Sopian, K., Yazdi, M.H., Ruslan, M.H., Ibrahim, A., Kazem, H.A.: Performance analysis of photovoltaic thermal (PVT) water collectors. Energy Convers. Manag. 78, 641–651 (2014)CrossRefGoogle Scholar
  10. 10.
    Tektaş, M.: Weather forecasting using ANFIS and ARIMA models. Environ. Res. Eng. Manag. 51, 5–10 (2010)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.School of Electrical EngineeringVITVelloreIndia

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