Abstract

Increasing the utilization of renewable energy is at the center of most sustainability policies. Solar energy is the most abundant resource of this type on Earth, and optimizing its use requires the optimal estimation of surface solar irradiation. Heliosat-2 is one of the most popular methods of global horizontal irradiation (GHI) estimation. Originally developed for the Meteosat satellite, Heliosat-2 has been modified in previous work to deal with GOES-13 data and named here GOES_H2. This model has been validated through the computation of indicators and irradiation maps for the Guiana Shield. This article proposes an improved version of GOES_H2, which has been combined with a radiative transfer parameterization (RTP) and the McClear clear-sky model (MC). This new version, hereafter designated RTP_MC_GOES_H2, was tested on eight stations from the Baseline Surface Radiation Network, located in North and South America, and covered by GOES-13. RTP_MC_GOES_H2 improves the hourly GHI estimates independently of the type of sky. This improvement is independent of the climate, no matter the station, the RTP_MC_GOES_H2 gives better results of MBE and RMSE than the original GOES_H2 method. Indeed, the MBE and RMSE values, respectively, change from −11.93% to −2.42% and 23.24% to 18.24% for North America and from −4.35% to 1.79% and 19.97% to 17.37 for South America. Moreover, the flexibility of the method may allow to improve results in the presence of snow cover and rainy/variable weather. Furthermore, RTP_MC_GOES_H2 results outperform or equalize those of other operational models.

Highlights

  • In light of the energy transition challenge, electricity production using renewable energy has received growing interest [1,2]

  • Assistance Program shows that the annual photovoltaic power potential is quite high for most countries [3]

  • Our work aims to generalize this approach to all types of climates and show that the global horizontal irradiation (GHI) estimation is improved under all skies

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Summary

Introduction

In light of the energy transition challenge, electricity production using renewable energy has received growing interest [1,2]. Maximizing solar radiation exploitation requires managing surface irradiation, namely, global horizontal irradiation (GHI) [4,5]. These data can be obtained in two main ways: in situ measurements [6] and estimation using satellite images [7]. Measurements are captured by instruments that require specific installation and continuous calibration and maintenance [8]. Satellite-based estimation is receiving increasing interest [9]

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