Photovoltaic prediction software: evaluation with real data from northern Spain

D González-Peña, I García-Ruiz, M Díez-Mediavilla… - Applied Sciences, 2021 - mdpi.com
D González-Peña, I García-Ruiz, M Díez-Mediavilla, MI Dieste-Velasco, C Alonso-Tristán
Applied Sciences, 2021mdpi.com
Featured Application Featured Application: Several commercially available and free
downloadable PV modelling software tools are compared with real data for three different
photovoltaic power plants in operation over the past 12 years. Both annual and monthly
results are analyzed. Abstract Prediction of energy production is crucial for the design and
installation of PV plants. In this study, five free and commercial software tools to predict
photovoltaic energy production are evaluated: RETScreen, Solar Advisor Model (SAM) …
Featured Application
Featured Application: Several commercially available and free downloadable PV modelling software tools are compared with real data for three different photovoltaic power plants in operation over the past 12 years. Both annual and monthly results are analyzed.
Abstract
Prediction of energy production is crucial for the design and installation of PV plants. In this study, five free and commercial software tools to predict photovoltaic energy production are evaluated: RETScreen, Solar Advisor Model (SAM), PVGIS, PVSyst, and PV*SOL. The evaluation involves a comparison of monthly and annually predicted data on energy supplied to the national grid with real field data collected from three real PV plants. All the systems, located in Castile and Leon (Spain), have three different tilting systems: fixed mounting, horizontal-axis tracking, and dual-axis tracking. The last 12 years of operating data, from 2008 to 2020, are used in the evaluation. Although the commercial software tools were easier to use and their installations could be described in detail, their results were not appreciably superior. In annual global terms, the results hid poor estimations throughout the year, where overestimations were compensated by underestimated results. This fact was reflected in the monthly results: the software yielded overestimates during the colder months, while the models showed better estimates during the warmer months. In most studies, the deviation was below 10% when the annual results were analyzed. The accuracy of the software was also reduced when the complexity of the dual-axis solar tracking systems replaced the fixed installation.
MDPI
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