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Condition Based Assessment and Diagnostics of Transformer in Smart Grid Network Using Adaptive Neuro Fuzzy Inference System Framework

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Intelligent Manufacturing and Energy Sustainability (ICIMES 2023)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 372))

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Abstract

In smart grid infrastructure, power transformers are one of the most integral assets that must be constantly monitored during their operational life. Several diagnostic methods, such as interfacial tension (IFT), moisture presence, degree of polymerization (DP), harmonics, temperature rise furans compound have detrimental effect on transformer insulation. This research article introduces a novel adaptive neural fuzzy inference system (ANFIS) model to analyse the insulation degradation for oil and paper based on the datasets of moisture contents, IFT, harmonics and temperature rise within the insulation. The proposed study findings are verified using real data gathered from various transformers used in utilities, industry and literatures including the impacts of electric vehicles (EV) and Distributed energy resources (DER). Time varying harmonics and temperature effect is important aspect of this research. The novel proposed ANFIS model is more than 90% efficient and errors of less than 1% for training and testing data sets utilized for study.

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Authors and Affiliations

  1. Department of Electrical Engineering, School of Energy Technology, Pandit Deendayal Energy University, Gandhinagar, Gujarat, 382426, India

    Rahul Soni & Bhinal Mehta

Authors
  1. Rahul Soni
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  2. Bhinal Mehta
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Corresponding author

Correspondence to Rahul Soni .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India

    P. H. V. Sesha Talpa Sai

  2. Department of Mechanical Engineering, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India

    Srikar Potnuru

  3. Faculty of Engineering, Department of Civil Engineering, Suleyman Demirel University, Isparta, Türkiye

    Mehmet Avcar

  4. Department of Mechanical Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India

    Vishesh Ranjan Kar

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Soni, R., Mehta, B. (2024). Condition Based Assessment and Diagnostics of Transformer in Smart Grid Network Using Adaptive Neuro Fuzzy Inference System Framework. In: Talpa Sai, P.H.V.S., Potnuru, S., Avcar, M., Ranjan Kar, V. (eds) Intelligent Manufacturing and Energy Sustainability. ICIMES 2023. Smart Innovation, Systems and Technologies, vol 372. Springer, Singapore. https://doi.org/10.1007/978-981-99-6774-2_13

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  • DOI: https://doi.org/10.1007/978-981-99-6774-2_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-6773-5

  • Online ISBN: 978-981-99-6774-2

  • eBook Packages: EngineeringEngineering (R0)

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