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A novel method for the determination of dynamic resistance for photovoltaic modules

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  • Wang, Jen-Cheng
  • Shieh, Jyh-Cherng
  • Su, Yu-Li
  • Kuo, Kun-Chang
  • Chang, Yen-Wei
  • Liang, Yu-Ting
  • Chou, Jui-Jen
  • Liao, Kuo-Chi
  • Jiang, Joe-Air

Abstract

Obtaining the maximum power output in real time is indispensable to the operation of grid connected photovoltaic (PV) power systems under given atmospheric conditions. Focusing on the resistance effect of the solar cells, we propose a new and simple method to directly determine the dynamic resistance of the PV modules from an irradiated current–voltage characteristic curve. In our method, we develop the ability to determine the dynamic resistance with a combination of finite series- and shunt-connected resistance. A series of experiments, including numerical simulations and field data tests, are conducted to examine the dynamic behavior of the PV modules during power tracking. Experimental results show that the proposed direct resistance-estimation method allows the PV modules to achieve their maximum power and impedance matching under various operation conditions.

Suggested Citation

  • Wang, Jen-Cheng & Shieh, Jyh-Cherng & Su, Yu-Li & Kuo, Kun-Chang & Chang, Yen-Wei & Liang, Yu-Ting & Chou, Jui-Jen & Liao, Kuo-Chi & Jiang, Joe-Air, 2011. "A novel method for the determination of dynamic resistance for photovoltaic modules," Energy, Elsevier, vol. 36(10), pages 5968-5974.
  • Handle: RePEc:eee:energy:v:36:y:2011:i:10:p:5968-5974
    DOI: 10.1016/j.energy.2011.08.019
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    3. Deihimi, M.H. & Naghizadeh, R.A. & Meyabadi, A. Fattahi, 2016. "Systematic derivation of parameters of one exponential model for photovoltaic modules using numerical information of data sheet," Renewable Energy, Elsevier, vol. 87(P1), pages 676-685.
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    5. Bizon, Nicu, 2013. "Energy harvesting from the PV Hybrid Power Source," Energy, Elsevier, vol. 52(C), pages 297-307.
    6. Dolara, Alberto & Lazaroiu, George Cristian & Leva, Sonia & Manzolini, Giampaolo, 2013. "Experimental investigation of partial shading scenarios on PV (photovoltaic) modules," Energy, Elsevier, vol. 55(C), pages 466-475.
    7. Kolesnik, Sergei & Sitbon, Moshe & Gadelovits, Shlomo & Suntio, Teuvo & Kuperman, Alon, 2015. "Interfacing renewable energy sources for maximum power transfer—Part II: Dynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1771-1783.
    8. Cotfas, D.T. & Cotfas, P.A. & Kaplanis, S., 2016. "Methods and techniques to determine the dynamic parameters of solar cells: Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 213-221.
    9. Kahoul, Nabil & Chenni, Rachid & Cheghib, Hocine & Mekhilef, Saad, 2017. "Evaluating the reliability of crystalline silicon photovoltaic modules in harsh environment," Renewable Energy, Elsevier, vol. 109(C), pages 66-72.
    10. Jiang, Joe-Air & Wang, Jen-Cheng & Kuo, Kun-Chang & Su, Yu-Li & Shieh, Jyh-Cherng & Chou, Jui-Jen, 2012. "Analysis of the junction temperature and thermal characteristics of photovoltaic modules under various operation conditions," Energy, Elsevier, vol. 44(1), pages 292-301.
    11. Yadav, Amit Kumar & Chandel, S.S., 2017. "Identification of relevant input variables for prediction of 1-minute time-step photovoltaic module power using Artificial Neural Network and Multiple Linear Regression Models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 955-969.

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