Abstract

The simulation of photovoltaic installations is a major issue for their sizing, their smart grid operation, and their fault detection and diagnosis. In this article, we study in detail every step of the simulation chain, either from the global horizontal irradiance and the ambient temperature (i.e., 4 steps of simulation) or considering the global in-plane irradiance and the module operating temperature (i.e., 1 step of simulation). The average quality estimation of the models is made through the calculations of average annual error between estimations and measurements, from 2016 to 2020. We have shown that the most uncertain step is the conversion of the global irradiance in its diffuse and direct components (17.2%, 2 models tested). If the model goes up to the in-plane irradiance, the average annual error decreases to 5.3% (6 models tested). The photovoltaic module temperature calculation induces an error of less than 2°C (4 models tested with 2 configurations). Meanwhile, the photoelectrical conversion shows a 3.5% error, similar to the measurement uncertainties, considering as input, the modules temperature, and the in-plane irradiance. If the simulation goes from the global irradiance and the ambient temperature measured locally, the estimation leads to a 6.7% average annual error. If the local measurements are not available, we can use the closest meteorological station’s records (13 for our study), and the error becomes 12.1%. Finally, we can also use the satellite images that lead to a 15.2% error, for average per year. The impact of available input shows that modeling the DC photovoltaic production, using global horizontal irradiance and ambient temperature, gives rise to an error of 6.6% for local measurements, 12.1% for weather station measurements, and 15.2% for satellite images estimations. This article thus draws up a review of the existing models, allowing to calculate the DC production of a photovoltaic module, depending on the atmospheric conditions, and highlights the most precise or most critical steps, considering in situ and weather station ground-based measurements, and also estimation from satellite images.

Highlights

  • Photovoltaic (PV) production mainly depends on the solar radiation incident on PV modules

  • This study focuses on the evaluation of the uncertainty on PV production estimation, step by step using different models, based on various data sources: in situ (SIRTA) and (ORLY) weather station ground-based measurements and geostationary satellite-based estimations (CAMS) during five years of operation

  • We firstly study the uncertainty of each successive step, just for SIRTA in situ ground-based measurements, in order to evaluate the propagation of the error and the most uncertain simulation stem

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Summary

Introduction

Photovoltaic (PV) production mainly depends on the solar radiation incident on PV modules. This study focuses on the evaluation of the uncertainty on PV production estimation, step by step using different models, based on various data sources: in situ (SIRTA) and (ORLY) weather station ground-based measurements and geostationary satellite-based estimations (CAMS) during five years of operation. The results are presented in Section 3: it deals with modeling error estimation for the whole PV system simulation focusing on the uncertainty weight of each step and considering different data sources These results are summarized in a conclusion and some perspectives are drawn

Experimental Data Sources
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Step 3
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Results
Conclusion
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