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Novel Application of Data-Driven Intelligent Approaches to Estimate Parameters of Photovoltaic Module for Condition Monitoring in Renewable Energy Systems

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Intelligent Data Analytics for Power and Energy Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 802))

Abstract

Photovoltaic (PV) arrays do not have moving parts. So, these require comparatively less maintenance. However, PV arrays operate under outdoor conditions in severe environment and lead to undergo different faults. Therefore, PV arrays’ fault diagnosis is necessary to make the PV energy systems more reliable. Due to varying environmental conditions and nonlinear PV characteristics, different artificial neural networks-based fault diagnosis has been proposed. But there are some concerns; e.g., fault diagnosis models are limited for mountainous region, and fault history is difficult to obtain using experimental analysis under outdoor condition. To address these concerns, this study proposes a new fault diagnostic techniques of PV module using extreme learning machine and multilayer feedforward neural network with Levenberg–Marquardt algorithm. For this, an experimental database of solar radiation, air and back surface module temperatures and electrical parameters of PV module are created by developing an experimental setup. This work is suitable for PV applications and researchers to estimate PV parameters for condition monitoring and would be useful for prior fault analysis of the PV module.

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Author information

Authors and Affiliations

  1. Electrical and Electronics Engineering, Raghu Engineering College (A), Visakhapatnam, 531162, India

    Omkar Singh

  2. Electrical and Electronics Engineering Department, National Institute of Technology Sikkim, Ravangla, Barfung Block, South Sikkim, 737139, India

    Omkar Singh, Amit Kumar Yadav & Anjan Kumar Ray

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  1. Omkar Singh
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  2. Amit Kumar Yadav
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  3. Anjan Kumar Ray
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Corresponding author

Correspondence to Amit Kumar Yadav .

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Editors and Affiliations

  1. BEARS, National University of Singapore (NUS), Singapore, Singapore

    Hasmat Malik

  2. Department of Electrical and Electronics Engineering, National Institute of Technology Karnataka, Surathkal, Karnataka, India

    Md. Waseem Ahmad

  3. THDC Institute of Hydropower Engineering and Technology, Chairman, Board of Governors, Tehri, Uttarakhand, India

    D.P. Kothari

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Singh, O., Yadav, A.K., Ray, A.K. (2022). Novel Application of Data-Driven Intelligent Approaches to Estimate Parameters of Photovoltaic Module for Condition Monitoring in Renewable Energy Systems. In: Malik, H., Ahmad, M.W., Kothari, D. (eds) Intelligent Data Analytics for Power and Energy Systems. Lecture Notes in Electrical Engineering, vol 802. Springer, Singapore. https://doi.org/10.1007/978-981-16-6081-8_21

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