Electricity Theft Detection and Localization in Smart Grids for Industry 4.0

被引:2
|
作者
Wisetsri, Worakamol [1 ]
Qamar, Shamimul [2 ]
Verma, Gaurav [3 ]
Verma, Deval [4 ]
Kakar, Varun Kumar [5 ]
Chansongpol, Thanyanant [6 ]
Somtawinpongsai, Chanyanan [6 ]
Tan, Chai Ching [7 ]
机构
[1] King Mongkuts Univ Technol North Bangkok KMUTNB, Fac Business & Ind Dev, Bangkok, Thailand
[2] King Khalid Univ, Coll Comp Sci, Comp Networks & Commun Engn, Abha, Saudi Arabia
[3] Jaypee Inst Informat Technol, Dept Elect & Commun Engn, Noida, India
[4] Chandigarh Univ, Dept UIS Math, Mohali, India
[5] BT Kumaon Inst Technol, Dept Elect & Commun, Dwarahat, India
[6] Rajapk Inst, Master Arts Program Art Management, Bangkok, Thailand
[7] Rajmangala Univ Technol, Rattanakosin Int Coll Creat Entrepreneurship, Rattanakosin, Thailand
来源
关键词
Smart grid; Industrial IoT; Industry; 4.0; Electricity theft; ThingSpeak cloud;
D O I
10.32604/iasc.2022.024610
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Industry 4.0 is considered as the fourth revolution in industrial sector that represents the digitization of production process in a smarter way. Industry 4.0 refers to the intelligent networking of machines, their processes, and infrastructure, as well as the use of information and computer technology to transform industry. The technologies like industrial internet of things (HoT), big data analytics, cloud computing, augmented reality and cyber security are the main pillars of industry 4.0. Industry 4.0, in particular, is strongly reliant on the IIoT that refers to the application of internet of things (IoT) in industrial sector like smart grids (SG). IoT can be deployed in different sections of smart grids that include electricity generation, transmission, distribution and its utilization at customer side. However, the key obstacles that deployment faces are theft detection and localization in smart grids. Electricity theft causes huge losses to the electricity providers and in turn contributes in increasing the fiscal deficit of the government. Therefore, this paper provides an IoT based solution that implements a system which automatically checks for electricity theft in between the regional transformer and customer side. The system also sends the latitude and longitude coordinates of the place where the theft has been detected on to the thingspeak cloud platform. Further, the exact location of the theft has been displayed on the webpage using geolocation application programing interface (API) on Google maps. The proposed system can be easily integrated in the smart grid network structure and helps companies to increase their business.
引用
收藏
页码:1473 / 1483
页数:11
相关论文
共 50 条
  • [1] Big Data Analytics for Electricity Theft Detection in Smart Grids
    Khan, Inam Ullah
    Javaid, Nadeem
    Taylor, C. James
    Gamage, Kelum A. A.
    Ma, Xiandong
    [J]. 2021 IEEE MADRID POWERTECH, 2021,
  • [2] Robust Detection of Electricity Theft Against Evasion Attacks in Smart Grids
    Takiddin, Abdulrahman
    Ismail, Muhammad
    Serpedin, Erchin
    [J]. IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021), 2021,
  • [3] Detection of Electricity Theft False Data Injection Attacks in Smart Grids
    Takiddin, Abdulrahman
    Ismail, Muhammad
    Serpedin, Erchin
    [J]. 2022 30TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2022), 2022, : 1541 - 1545
  • [4] Detection of Energy Theft in Smart Grids using Electricity Consumption Patterns
    Syed, Dabeeruddin
    Abu-Rub, Haitham
    Refaat, Shady S.
    Xie, Le
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2020, : 4059 - 4064
  • [5] Electricity Theft Detection in Smart Grids Based on Deep Neural Network
    Lepolesa, Leloko J.
    Achari, Shamin
    Cheng, Ling
    [J]. IEEE ACCESS, 2022, 10 : 39638 - 39655
  • [6] Smart Grids and Industry 4.0
    Tuttokmagi, Ozge
    Kaygusuz, Asim
    [J]. 2018 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND DATA PROCESSING (IDAP), 2018,
  • [7] A Novel Multivariate and Accurate Detection Scheme for Electricity Theft Attacks in Smart Grids
    Abdellatif, Alaa Awad
    Amer, Aya
    Shaban, Khaled
    Massoud, Ahmed
    [J]. 2023 INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKING AND COMMUNICATIONS, ICNC, 2023, : 558 - 562
  • [8] A practical feature-engineering framework for electricity theft detection in smart grids
    Razavi, Rouzbeh
    Gharipour, Amin
    Fleury, Martin
    Akpan, Ikpe Justice
    [J]. APPLIED ENERGY, 2019, 238 : 481 - 494
  • [9] Hybrid CNN-Transformer Network for Electricity Theft Detection in Smart Grids
    Bai, Yu
    Sun, Haitong
    Zhang, Lili
    Wu, Haoqi
    [J]. SENSORS, 2023, 23 (20)
  • [10] Electricity Theft Detection Using Deep Reinforcement Learning in Smart Power Grids
    El-Toukhy, Ahmed T.
    Badr, Mahmoud M.
    Mahmoud, Mohamed M. E. A.
    Srivastava, Gautam
    Fouda, Mostafa M.
    Alsabaan, Maazen
    [J]. IEEE ACCESS, 2023, 11 : 59558 - 59574