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A Characterization of Metrics for Comparing Satellite-Based and Ground-Measured Global Horizontal Irradiance Data: A Principal Component Analysis Application

Author

Listed:
  • Maria. C. Bueso

    (Department of Applied Mathematics and Statistics, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain
    These authors contributed equally to this work.)

  • José Miguel Paredes-Parra

    (Technologic Center of Energy and Environment, 30202 Cartagena, Spain
    These authors contributed equally to this work.)

  • Antonio Mateo-Aroca

    (Department of Automatic, Electrical Engineering and Electronic Technology, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain
    These authors contributed equally to this work.)

  • Angel Molina-García

    (Department of Automatic, Electrical Engineering and Electronic Technology, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain
    These authors contributed equally to this work.)

Abstract

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.

Suggested Citation

  • Maria. C. Bueso & José Miguel Paredes-Parra & Antonio Mateo-Aroca & Angel Molina-García, 2020. "A Characterization of Metrics for Comparing Satellite-Based and Ground-Measured Global Horizontal Irradiance Data: A Principal Component Analysis Application," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2454-:d:334985
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    1. Maldonado-Salguero, Patricia & Bueso-Sánchez, María Carmen & Molina-García, Ángel & Sánchez-Lozano, Juan Miguel, 2022. "Spatio-temporal dynamic clustering modeling for solar irradiance resource assessment," Renewable Energy, Elsevier, vol. 200(C), pages 344-359.

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