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<dc:title>Photovoltaic Prediction Software: Evaluation with Real Data from Northern Spain</dc:title>
<dc:creator>González Peña, David</dc:creator>
<dc:creator>García Ruiz, Ignacio</dc:creator>
<dc:creator>Diez Mediavilla, Montserrat</dc:creator>
<dc:creator>Dieste Velasco, Mª Isabel</dc:creator>
<dc:creator>Alonso Tristán, Cristina</dc:creator>
<dc:subject>Photovoltaic</dc:subject>
<dc:subject>RETScreen</dc:subject>
<dc:subject>SAM</dc:subject>
<dc:subject>PVGIS</dc:subject>
<dc:subject>PVsyst</dc:subject>
<dc:subject>PV*SOL</dc:subject>
<dc:subject>Energy prediction</dc:subject>
<dc:description>Prediction of energy production is crucial for the design and installation of PV plants. In&#xd;
this study, five free and commercial software tools to predict photovoltaic energy production are&#xd;
evaluated: RETScreen, Solar Advisor Model (SAM), PVGIS, PVSyst, and PV*SOL. The evaluation&#xd;
involves a comparison of monthly and annually predicted data on energy supplied to the national&#xd;
grid with real field data collected from three real PV plants. All the systems, located in Castile and&#xd;
Leon (Spain), have three different tilting systems: fixed mounting, horizontal-axis tracking, and&#xd;
dual-axis tracking. The last 12 years of operating data, from 2008 to 2020, are used in the evaluation.&#xd;
Although the commercial software tools were easier to use and their installations could be described&#xd;
in detail, their results were not appreciably superior. In annual global terms, the results hid poor&#xd;
estimations throughout the year, where overestimations were compensated by underestimated&#xd;
results. This fact was reflected in the monthly results: the software yielded overestimates during&#xd;
the colder months, while the models showed better estimates during the warmer months. In most&#xd;
studies, the deviation was below 10% when the annual results were analyzed. The accuracy of the&#xd;
software was also reduced when the complexity of the dual-axis solar tracking systems replaced the&#xd;
fixed installation.</dc:description>
<dc:date>2023-01-19T10:22:51Z</dc:date>
<dc:date>2023-01-19T10:22:51Z</dc:date>
<dc:date>2021-05</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:identifier>http://hdl.handle.net/10259/7273</dc:identifier>
<dc:identifier>10.3390/app11115025</dc:identifier>
<dc:identifier>2076-3417</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Applied sciences. 2021, V. 11, n. 11, 5025</dc:relation>
<dc:relation>https://doi.org/10.3390/app11115025</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098900-B-I00/ES/ANALISIS ESPECTRAL DE LA RADIACION SOLAR: APLICACIONES CLIMATICAS, ENERGETICAS Y BIOLOGICAS/</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/Junta de Castilla y León//INVESTUN%2F19%2FBU%2F0004//Valoración técnica de los niveles de exposición a radiación solar en trabajos de exterior: identificación de grupos de riesgo y medidas de prevención/</dc:relation>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>Atribución 4.0 Internacional</dc:rights>
<dc:publisher>MDPI</dc:publisher>
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