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Modelling and estimating performance for PV module under varying operating conditions independent of reference condition

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  • Zhang, Yunpeng
  • Hao, Peng
  • Lu, Hao
  • Ma, Jiao
  • Yang, Ming

Abstract

Existing methods for parameter identification and performance estimation under varying operating conditions are accomplished in two steps: first, the model parameters are extracted under the prescribed reference condition; second, the model parameters under varying operating conditions are calculated based on the dependence of parameters on environmental conditions. There are two disadvantages for existing methods: the results are affected by the selection of reference condition, and the irradiance and temperature dependence of parameters are non-uniform for different types PV modules. This paper studies the effect of the reference condition selection and proposes a novel method for parameter identification and performance estimation under varying operating conditions. In the proposed method, a set of improved transformation equations are modified by considering both irradiance and temperature dependence for all parameters in single-diode model (SDM). Since the improved transformation equations are independent of reference condition, the effect of the selection of reference condition is eliminated. The coefficients of the improved transformation equations are extracted through guaranteed convergence particle swarm optimization technology from measured I-V curves under different operating conditions. The efficiency and accuracy of proposed method is validated by amount of experimental data under different irradiance and temperature conditions for different types of PV modules. The variations of SDM’s parameters by the proposed method have been investigated thoroughly and shown to be in accordance with the physical behavior of the PV devices. The proposed method can be further employed to simulate the performance of a PV module under real operating conditions and exhibits great accuracy and suitability.

Suggested Citation

  • Zhang, Yunpeng & Hao, Peng & Lu, Hao & Ma, Jiao & Yang, Ming, 2022. "Modelling and estimating performance for PV module under varying operating conditions independent of reference condition," Applied Energy, Elsevier, vol. 310(C).
  • Handle: RePEc:eee:appene:v:310:y:2022:i:c:s0306261922000162
    DOI: 10.1016/j.apenergy.2022.118527
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    References listed on IDEAS

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    1. Abbassi, Rabeh & Abbassi, Abdelkader & Jemli, Mohamed & Chebbi, Souad, 2018. "Identification of unknown parameters of solar cell models: A comprehensive overview of available approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 453-474.
    2. Lim, Li Hong Idris & Ye, Zhen & Ye, Jiaying & Yang, Dazhi & Du, Hui, 2015. "A linear method to extract diode model parameters of solar panels from a single I–V curve," Renewable Energy, Elsevier, vol. 76(C), pages 135-142.
    3. Nunes, H.G.G. & Pombo, J.A.N. & Mariano, S.J.P.S. & Calado, M.R.A. & Felippe de Souza, J.A.M., 2018. "A new high performance method for determining the parameters of PV cells and modules based on guaranteed convergence particle swarm optimization," Applied Energy, Elsevier, vol. 211(C), pages 774-791.
    4. Aly, Shahzada Pamir & Ahzi, Said & Barth, Nicolas, 2019. "An adaptive modelling technique for parameters extraction of photovoltaic devices under varying sunlight and temperature conditions," Applied Energy, Elsevier, vol. 236(C), pages 728-742.
    5. Celik, Ali Naci & Acikgoz, NasIr, 2007. "Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four- and five-parameter models," Applied Energy, Elsevier, vol. 84(1), pages 1-15, January.
    6. Chenni, R. & Makhlouf, M. & Kerbache, T. & Bouzid, A., 2007. "A detailed modeling method for photovoltaic cells," Energy, Elsevier, vol. 32(9), pages 1724-1730.
    7. Cuce, Erdem & Cuce, Pinar Mert & Bali, Tulin, 2013. "An experimental analysis of illumination intensity and temperature dependency of photovoltaic cell parameters," Applied Energy, Elsevier, vol. 111(C), pages 374-382.
    8. Khan, Firoz & Baek, Seong-Ho & Kim, Jae Hyun, 2014. "Intensity dependency of photovoltaic cell parameters under high illumination conditions: An analysis," Applied Energy, Elsevier, vol. 133(C), pages 356-362.
    9. Askarzadeh, Alireza & Rezazadeh, Alireza, 2013. "Artificial bee swarm optimization algorithm for parameters identification of solar cell models," Applied Energy, Elsevier, vol. 102(C), pages 943-949.
    10. AlHajri, M.F. & El-Naggar, K.M. & AlRashidi, M.R. & Al-Othman, A.K., 2012. "Optimal extraction of solar cell parameters using pattern search," Renewable Energy, Elsevier, vol. 44(C), pages 238-245.
    11. Khan, Firoz & Baek, Seong-Ho & Kim, Jae Hyun, 2016. "Wide range temperature dependence of analytical photovoltaic cell parameters for silicon solar cells under high illumination conditions," Applied Energy, Elsevier, vol. 183(C), pages 715-724.
    12. Li, Shuijia & Gong, Wenyin & Gu, Qiong, 2021. "A comprehensive survey on meta-heuristic algorithms for parameter extraction of photovoltaic models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
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    1. Lu, Yashun & Li, Guiqiang, 2023. "Potential application of electrical performance enhancement methods in PV/T module," Energy, Elsevier, vol. 281(C).

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