A novel deep learning technique to detect electricity theft in smart grids using AlexNet Article Swipe
Nitasha Khan
,
Zeeshan Shahid
,
Muhammad Mansoor Alam
,
Aznida Abu Bakar Sajak
,
Mobeen Nazar
,
Mazliham Mohd Su’ud
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1049/rpg2.12846
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1049/rpg2.12846
Electricity theft (ET), which endangers public safety, interferes with the regular operation of grid infrastructure, and increases revenue losses, is a significant issue for power companies. To find ET, numerous machine learning, deep learning, and mathematically based algorithms have been published in the literature. However, these models do not yield the greatest results due to issues like the dimensionality curse, class imbalance, inappropriate hyper‐parameter tuning of machine learning, deep learning models etc. A hybrid DL model is presented for effectively detecting electricity thieves in smart grids while considering the abovementioned concerns. Pre‐processing techniques are first employed to clean up the data from the smart meters, and then the feature extraction technique, AlexNet is used to address the curse of dimensionality. An actual dataset of Chinese smart meters is used in simulations to assess the efficacy of the suggested approach. To conduct a comparative analysis, various benchmark models are implemented as well. This proposed model achieves accuracy, precision, recall, and F1‐score, up to 86%, 89%, 86%, and 84%, respectively.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/rpg2.12846
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/rpg2.12846
- OA Status
- gold
- Cited By
- 9
- References
- 49
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391781022
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391781022Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1049/rpg2.12846Digital Object Identifier
- Title
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A novel deep learning technique to detect electricity theft in smart grids using AlexNetWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-02-13Full publication date if available
- Authors
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Nitasha Khan, Zeeshan Shahid, Muhammad Mansoor Alam, Aznida Abu Bakar Sajak, Mobeen Nazar, Mazliham Mohd Su’udList of authors in order
- Landing page
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https://doi.org/10.1049/rpg2.12846Publisher landing page
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/rpg2.12846Direct link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/rpg2.12846Direct OA link when available
- Concepts
-
Computer science, Electricity, Smart grid, Artificial intelligence, Deep learning, Computer security, Engineering, Electrical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
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2025: 4, 2024: 5Per-year citation counts (last 5 years)
- References (count)
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49Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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