A characterization of metrics for comparing satellite-based and ground-measured global horizontal irradiance data: A principal component analysis application

Journal ar
Sustainability (Switzerland)
  • Volumen: 12
  • Número: 6
  • Fecha: 01 marzo 2020
  • ISSN: 20711050
  • Tipo de fuente: Revista
  • DOI: 10.3390/su12062454
  • Tipo de documento: Artículo
  • Editorial: MDPI
© 2020 by the authors.The increasing integration of photovoltaic (PV) power plants into power systems demands a high accuracy of yield prediction and measurement. With this aim, different global horizontal irradiance (GHI) estimations based on new-generation geostationary satellites have been recently proposed, providing a growing number of solutions and databases, mostly available online, in addition to the many ground-based irradiance data installations currently available. According to the specific literature, there is a lack of agreement in validation strategies for a bankable, satellite-derived irradiance dataset. Moreover, different irradiance data sources are compared in recent contributions based on a diversity of arbitrary metrics. Under this framework, this paper describes a characterization of metrics based on a principal component analysis (PCA) application to classify such metrics, aiming to provide non-redundant and complementary information. Therefore, different groups of metrics are identified by applying the PCA process, allowing us to compare, in a more extensive way, different irradiance data sources and exploring and identifying their differences. The methodology has been evaluated using satellite-based and ground-measured GHI data collected for one year in seven different Spanish locations, with a one-hour sample time. Data characterization, results, and a discussion about the suitability of the proposed methodology are also included in the paper.

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