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Electricity Theft Detection in Smart Grid Systems: A CNN-LSTM Based Approach

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Cited by:

  1. Athanasiadis, C.L. & Papadopoulos, T.A. & Kryonidis, G.C. & Doukas, D.I., 2024. "A review of distribution network applications based on smart meter data analytics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
  2. Sufian A. Badawi & Djamel Guessoum & Isam Elbadawi & Ameera Albadawi, 2022. "A Novel Time-Series Transformation and Machine-Learning-Based Method for NTL Fraud Detection in Utility Companies," Mathematics, MDPI, vol. 10(11), pages 1-16, May.
  3. Cheong Hee Park & Taegong Kim, 2020. "Energy Theft Detection in Advanced Metering Infrastructure Based on Anomaly Pattern Detection," Energies, MDPI, vol. 13(15), pages 1-10, July.
  4. Akram Qashou & Sufian Yousef & Firas Hazzaa & Kahtan Aziz, 2024. "Temporal forecasting by converting stochastic behaviour into a stable pattern in electric grid," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(9), pages 4426-4442, September.
  5. Xiaofeng Feng & Hengyu Hui & Ziyang Liang & Wenchong Guo & Huakun Que & Haoyang Feng & Yu Yao & Chengjin Ye & Yi Ding, 2020. "A Novel Electricity Theft Detection Scheme Based on Text Convolutional Neural Networks," Energies, MDPI, vol. 13(21), pages 1-17, November.
  6. Gao, Bixuan & Kong, Xiangyu & Li, Shangze & Chen, Yi & Zhang, Xiyuan & Liu, Ziyu & Lv, Weijia, 2024. "Enhancing anomaly detection accuracy and interpretability in low-quality and class imbalanced data: A comprehensive approach," Applied Energy, Elsevier, vol. 353(PB).
  7. Hugo Brise o & Omar Rojas, 2020. "Factors Associated with Electricity Losses: A Panel Data Perspective," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 281-286.
  8. Francisco Jonatas Siqueira Coelho & Allan Rivalles Souza Feitosa & André Luís Michels Alcântara & Kaifeng Li & Ronaldo Ferreira Lima & Victor Rios Silva & Abel Guilhermino da Silva-Filho, 2023. "HyMOTree: Automatic Hyperparameters Tuning for Non-Technical Loss Detection Based on Multi-Objective and Tree-Based Algorithms," Energies, MDPI, vol. 16(13), pages 1-22, June.
  9. Weijia Wen & Xiao Ling & Jianxin Sui & Junjie Lin, 2023. "Data-Driven Dynamic Stability Assessment in Large-Scale Power Grid Based on Deep Transfer Learning," Energies, MDPI, vol. 16(3), pages 1-15, January.
  10. Pamir & Nadeem Javaid & Saher Javaid & Muhammad Asif & Muhammad Umar Javed & Adamu Sani Yahaya & Sheraz Aslam, 2022. "Synthetic Theft Attacks and Long Short Term Memory-Based Preprocessing for Electricity Theft Detection Using Gated Recurrent Unit," Energies, MDPI, vol. 15(8), pages 1-20, April.
  11. Hany Habbak & Mohamed Mahmoud & Mostafa M. Fouda & Maazen Alsabaan & Ahmed Mattar & Gouda I. Salama & Khaled Metwally, 2023. "Efficient One-Class False Data Detector Based on Deep SVDD for Smart Grids," Energies, MDPI, vol. 16(20), pages 1-28, October.
  12. Youngghyu Sun & Jiyoung Lee & Soohyun Kim & Joonho Seon & Seongwoo Lee & Chanuk Kyeong & Jinyoung Kim, 2023. "Energy Theft Detection Model Based on VAE-GAN for Imbalanced Dataset," Energies, MDPI, vol. 16(3), pages 1-13, January.
  13. Barja-Martinez, Sara & Aragüés-Peñalba, Mònica & Munné-Collado, Íngrid & Lloret-Gallego, Pau & Bullich-Massagué, Eduard & Villafafila-Robles, Roberto, 2021. "Artificial intelligence techniques for enabling Big Data services in distribution networks: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
  14. Zahoor Ali Khan & Muhammad Adil & Nadeem Javaid & Malik Najmus Saqib & Muhammad Shafiq & Jin-Ghoo Choi, 2020. "Electricity Theft Detection Using Supervised Learning Techniques on Smart Meter Data," Sustainability, MDPI, vol. 12(19), pages 1-25, September.
  15. Lisardo Prieto González & Anna Fensel & Juan Miguel Gómez Berbís & Angela Popa & Antonio de Amescua Seco, 2021. "A Survey on Energy Efficiency in Smart Homes and Smart Grids," Energies, MDPI, vol. 14(21), pages 1-16, November.
  16. Otuoze, Abdulrahaman Okino & Mustafa, Mohd Wazir & Abdulrahman, Abdulhakeem Temitope & Mohammed, Olatunji Obalowu & Salisu, Sani, 2020. "Penalization of electricity thefts in smart utility networks by a cost estimation-based forced corrective measure," Energy Policy, Elsevier, vol. 143(C).
  17. Zeeshan Aslam & Nadeem Javaid & Ashfaq Ahmad & Abrar Ahmed & Sardar Muhammad Gulfam, 2020. "A Combined Deep Learning and Ensemble Learning Methodology to Avoid Electricity Theft in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-24, October.
  18. Konstantinos V. Blazakis & Theodoros N. Kapetanakis & George S. Stavrakakis, 2020. "Effective Electricity Theft Detection in Power Distribution Grids Using an Adaptive Neuro Fuzzy Inference System," Energies, MDPI, vol. 13(12), pages 1-13, June.
  19. Theyazn H. H. Aldhyani & Hasan Alkahtani, 2023. "Cyber Security for Detecting Distributed Denial of Service Attacks in Agriculture 4.0: Deep Learning Model," Mathematics, MDPI, vol. 11(1), pages 1-19, January.
  20. Mitra, Somalee & Chakraborty, Basab & Mitra, Pabitra, 2024. "Smart meter data analytics applications for secure, reliable and robust grid system: Survey and future directions," Energy, Elsevier, vol. 289(C).
  21. Marcelo Bruno Capeletti & Bruno Knevitz Hammerschmitt & Renato Grethe Negri & Fernando Guilherme Kaehler Guarda & Lucio Rene Prade & Nelson Knak Neto & Alzenira da Rosa Abaide, 2022. "Identification of Nontechnical Losses in Distribution Systems Adding Exogenous Data and Artificial Intelligence," Energies, MDPI, vol. 15(23), pages 1-23, November.
  22. Xuesong Tian & Yuping Zou & Xin Wang & Minglang Tseng & Hua Li & Huijuan Zhang, 2022. "Improving the Efficiency and Sustainability of Intelligent Electricity Inspection: IMFO-ELM Algorithm for Load Forecasting," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
  23. Rui Xia & Yunpeng Gao & Yanqing Zhu & Dexi Gu & Jiangzhao Wang, 2022. "An Efficient Method Combined Data-Driven for Detecting Electricity Theft with Stacking Structure Based on Grey Relation Analysis," Energies, MDPI, vol. 15(19), pages 1-25, October.
  24. Akram Qashou & Sufian Yousef & Erika Sanchez-Velazquez, 2022. "Mining sensor data in a smart environment: a study of control algorithms and microgrid testbed for temporal forecasting and patterns of failure," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2371-2390, October.
  25. Tehseen Mazhar & Hafiz Muhammad Irfan & Sunawar Khan & Inayatul Haq & Inam Ullah & Muhammad Iqbal & Habib Hamam, 2023. "Analysis of Cyber Security Attacks and Its Solutions for the Smart grid Using Machine Learning and Blockchain Methods," Future Internet, MDPI, vol. 15(2), pages 1-37, February.
  26. Taha Selim Ustun, 2022. "Cybersecurity in Smart Grids," Energies, MDPI, vol. 15(15), pages 1-3, July.
  27. Adnan Khattak & Rasool Bukhsh & Sheraz Aslam & Ayman Yafoz & Omar Alghushairy & Raed Alsini, 2022. "A Hybrid Deep Learning-Based Model for Detection of Electricity Losses Using Big Data in Power Systems," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
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