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Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance

Author

Listed:
  • Alba Vilanova

    (New-Renewable Energy Resource & Policy Center, Korea Institute of Energy Research, Daejeon 34129, Korea
    Higher Polytechnic School, University of Lleida, 25001 Lleida, Spain)

  • Bo-Young Kim

    (New-Renewable Energy Resource & Policy Center, Korea Institute of Energy Research, Daejeon 34129, Korea)

  • Chang Ki Kim

    (New-Renewable Energy Resource & Policy Center, Korea Institute of Energy Research, Daejeon 34129, Korea)

  • Hyun-Goo Kim

    (New-Renewable Energy Resource & Policy Center, Korea Institute of Energy Research, Daejeon 34129, Korea)

Abstract

A simple yet accurate photovoltaic (PV) performance curve as a function of satellite-based solar irradiation is necessary to develop a PV power forecasting model that can cover all of South Korea, where more than 35,000 PV power plants are currently in operation. In order to express the nonlinear power output of the PV module with respect to the hourly global horizontal irradiance derived from satellite images, this study employed the Gompertz model, which is composed of three parameters and the sigmoid equation. The nonphysical behavior of the Gompertz model within the low solar irradiation range was corrected by combining a linear equation with the same gradient at the conjoint point. The overall fitness of Linear-Gompertz regression to the 242 PV power plants representing the country was R 2 = 0.85 and nRMSE = 0.09. The Gompertz model coefficients showed normal distributions and equivariance of standard deviations of less than 15% by year and by season. Therefore, it can be conjectured that the Linear-Gompertz model represents the whole country’s PV system performance curve. In addition, the Gompertz coefficient C, which controls the growth rate of the curve, showed a strong correlation with the capacity factor, such that the regression equation for the capacity factor could be derived as a function of the three Gompertz model coefficients with a fitness of R 2 = 0.88.

Suggested Citation

  • Alba Vilanova & Bo-Young Kim & Chang Ki Kim & Hyun-Goo Kim, 2020. "Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance," Energies, MDPI, vol. 13(4), pages 1-12, February.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:4:p:781-:d:319116
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    References listed on IDEAS

    as
    1. Alexander Maennel & Hyun-Goo Kim, 2018. "Comparison of Greenhouse Gas Reduction Potential through Renewable Energy Transition in South Korea and Germany," Energies, MDPI, vol. 11(1), pages 1-12, January.
    2. Alberto Bocca & Luca Bergamasco & Matteo Fasano & Lorenzo Bottaccioli & Eliodoro Chiavazzo & Alberto Macii & Pietro Asinari, 2018. "Multiple-Regression Method for Fast Estimation of Solar Irradiation and Photovoltaic Energy Potentials over Europe and Africa," Energies, MDPI, vol. 11(12), pages 1-17, December.
    3. Das, Utpal Kumar & Tey, Kok Soon & Seyedmahmoudian, Mehdi & Mekhilef, Saad & Idris, Moh Yamani Idna & Van Deventer, Willem & Horan, Bend & Stojcevski, Alex, 2018. "Forecasting of photovoltaic power generation and model optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 912-928.
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