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  • Open Access

    ARTICLE

    Energy Theft Detection in Smart Grids with Genetic Algorithm-Based Feature Selection

    Muhammad Umair1,*, Zafar Saeed1, Faisal Saeed2, Hiba Ishtiaq1, Muhammad Zubair1, Hala Abdel Hameed3,4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5431-5446, 2023, DOI:10.32604/cmc.2023.033884

    Abstract As big data, its technologies, and application continue to advance, the Smart Grid (SG) has become one of the most successful pervasive and fixed computing platforms that efficiently uses a data-driven approach and employs efficient information and communication technology (ICT) and cloud computing. As a result of the complicated architecture of cloud computing, the distinctive working of advanced metering infrastructures (AMI), and the use of sensitive data, it has become challenging to make the SG secure. Faults of the SG are categorized into two main categories, Technical Losses (TLs) and Non-Technical Losses (NTLs). Hardware failure,… More >

  • Open Access

    ARTICLE

    Electricity Theft Detection and Localization in Smart Grids for Industry 4.0

    Worakamol Wisetsri1, Shamimul Qamar2, Gaurav Verma3,*, Deval Verma4, Varun Kumar Kakar5, Thanyanant Chansongpol6, Chanyanan Somtawinpongsai6, Chai Ching Tan7

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1473-1483, 2022, DOI:10.32604/iasc.2022.024610

    Abstract 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 (IIoT), 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… More >

  • Open Access

    ARTICLE

    Energy Theft Identification Using Adaboost Ensembler in the Smart Grids

    Muhammad Irfan1,*, Nasir Ayub2, Faisal Althobiani3, Zain Ali4, Muhammad Idrees5, Saeed Ullah2, Saifur Rahman1, Abdullah Saeed Alwadie1, Saleh Mohammed Ghonaim3, Hesham Abdushkour3, Fahad Salem Alkahtani1, Samar Alqhtani6, Piotr Gas7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2141-2158, 2022, DOI:10.32604/cmc.2022.025466

    Abstract One of the major concerns for the utilities in the Smart Grid (SG) is electricity theft. With the implementation of smart meters, the frequency of energy usage and data collection from smart homes has increased, which makes it possible for advanced data analysis that was not previously possible. For this purpose, we have taken historical data of energy thieves and normal users. To avoid imbalance observation, biased estimates, we applied the interpolation method. Furthermore, the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further processing.… More >

  • Open Access

    ARTICLE

    Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

    Lijo Jacob Varghese1, K. Dhayalini2, Suma Sira Jacob3, Ihsan Ali4,*, Abdelzahir Abdelmaboud5, Taiseer Abdalla Elfadil Eisa6

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1053-1067, 2022, DOI:10.32604/cmc.2022.019435

    Abstract Peer-to-Peer (P2P) electricity trading is a significant research area that offers maximum fulfilment for both prosumer and consumer. It also decreases the quantity of line loss incurred in Smart Grid (SG). But, uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and consumer. In recent times, numerous Machine Learning (ML)-enabled load predictive techniques have been developed, while most of the existing studies did not consider its implicit features, optimal parameter selection, and prediction stability. In order to overcome fulfill this research gap, the current research paper… More >

  • Open Access

    ARTICLE

    Earth Fault Management for Smart Grids Interconnecting Sustainable Wind Generation

    Nagy I. Elkalashy*, Sattam Al Otaibi, Salah K. Elsayed, Yasser Ahmed, Essam Hendawi, Ayman Hoballah

    Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 477-491, 2021, DOI:10.32604/iasc.2021.016558

    Abstract In this study, the active traveling-wave fault location function is incorporated into the management of earth faults for smart unearthed and compensated distribution networks associated with distributed renewable generation. Unearthed and compensated networks are implemented mainly to attain service continuity, specifically during earth faults. This advantage is valued for service continuity of grid-interconnected renewable resources. However, overcurrent-based fault indicators are not efficient in indicating the fault path in these distribution networks. Accordingly, in this study, the active traveling-wave fault location is complemented using distributed Rogowski coil-based fault passage indicators. Active traveling waves are injected by… More >

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