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

• Main Authors: Alba Vilanova, Bo-Young Kim, Chang Ki Kim, Hyun-Goo Kim
• Format: Article
• Language: English
• Published: MDPI AG 2020-02-01
• Series: Energies
• Subjects: photovoltaic system performance; power output prediction; satellite-derived global horizontal irradiance; numerical analysis; gompertz model
• Online Access: https://www.mdpi.com/1996-1073/13/4/781

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 R² = 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 R² = 0.88.