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Measurement of Thermal and Electrical Parameters in Photovoltaic Systems for Predictive and Cross-Correlated Monitorization

Author

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  • Carlos Toledo

    (Departamento de Electrónica, Universidad Politécnica de Cartagena, Plaza del Hospital 1, 30202 Cartagena, Spain)

  • Lucía Serrano-Lujan

    (Departamento de Ciencias de la Computación, Arquitectura de Computadores, Lenguajes y Sistemas Informáticos y Estadística e Investigación Operativa, Universidad Rey Juan Carlos, Calle Tulipán s/n, Móstoles, 28933 Madrid, Spain)

  • Jose Abad

    (Departamento de Física Aplicada, Universidad Politécnica de Cartagena, Calle Doctor Fleming, s/n, 30202 Cartagena, Spain)

  • Antonio Lampitelli

    (Departamento de Electrónica, Universidad Politécnica de Cartagena, Plaza del Hospital 1, 30202 Cartagena, Spain)

  • Antonio Urbina

    (Departamento de Electrónica, Universidad Politécnica de Cartagena, Plaza del Hospital 1, 30202 Cartagena, Spain)

Abstract

Photovoltaic electricity generation is growing at an almost exponential rate worldwide, reaching 400 GW p of installed capacity in 2018. Different types of installations, ranging from small building integrated systems to large plants, require different maintenance strategies, including strategies for monitorization and data processing. In this article, we present three case studies at different scales (from hundreds of W p to a 2.1 MW p plant), where automated parameter monitorization and data analysis has been carried out, aiming to detect failures and provide recommendations for optimum maintenance procedures. For larger systems, the data collected by the inverters provides the best source of information, and the cross-correlated analysis which uses these data is the best strategy to detect failures in module strings and failures in the inverters themselves (an average of 32.2% of inverters with failures was found after ten years of operation). In regards to determining which module is failing, the analysis of thermographic images is reliable and allows the detection of the failed module within the string (up to 1.5% for grave failures and 9.1% of medium failures for the solar plant after eleven years of activity). Photovoltaic (PV) systems at different scales require different methods for monitorization: Medium and large systems depend on inverter automated data acquisition, which can be complemented with thermographic images. Nevertheless, if the purpose of the monitorization is to obtain detailed information about the degradation processes of the solar cells, it becomes necessary to measure the environmental (irradiance and ambient temperature), thermal and electrical parameters (I-V characterization) of the modules and compare the experimental data with the modelling results. This is only achievable in small systems.

Suggested Citation

  • Carlos Toledo & Lucía Serrano-Lujan & Jose Abad & Antonio Lampitelli & Antonio Urbina, 2019. "Measurement of Thermal and Electrical Parameters in Photovoltaic Systems for Predictive and Cross-Correlated Monitorization," Energies, MDPI, vol. 12(4), pages 1-20, February.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:668-:d:207176
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    References listed on IDEAS

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    1. Serrano-Luján, L. & Toledo, C. & Colmenar, J.M. & Abad, J. & Urbina, A., 2022. "Accurate thermal prediction model for building-integrated photovoltaics systems using guided artificial intelligence algorithms," Applied Energy, Elsevier, vol. 315(C).
    2. Carlos Toledo & Ana Maria Gracia Amillo & Giorgio Bardizza & Jose Abad & Antonio Urbina, 2020. "Evaluation of Solar Radiation Transposition Models for Passive Energy Management and Building Integrated Photovoltaics," Energies, MDPI, vol. 13(3), pages 1-24, February.

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