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Yuefei Sun, Xianbo Sun, Tao Hu and Li Zhu
Despite the widespread use of artificial intelligence-based methods in detecting electricity theft by smart grid customers, current methods suffer from two main flaws: a limited amount of data on electricity theft customers compared to that on normal cus...
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Nasir Ayub, Usman Ali, Kainat Mustafa, Syed Muhammad Mohsin and Sheraz Aslam
In the smart grid (SG), user consumption data are increasing very rapidly. Some users consume electricity legally, while others steal it. Electricity theft causes significant damage to power grids, affects power supply efficiency, and reduces utility rev...
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Armin Razmjoo, Amirhossein Gandomi, Maral Mahlooji, Davide Astiaso Garcia, Seyedali Mirjalili, Alireza Rezvani, Sahar Ahmadzadeh and Saim Memon
As smart cities (SCs) emerge, the Internet of Things (IoT) is able to simplify more sophisticated and ubiquitous applications employed within these cities. In this regard, we investigate seven predominant sectors including the environment, public transpo...
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Rajiv Punmiya and Sangho Choe
Smart Grid (SG); Smart City; Demand Side Management (DSM); Building Energy Management System; Home Energy Management System.
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Muhammad Adil, Nadeem Javaid, Umar Qasim, Ibrar Ullah, Muhammad Shafiq and Jin-Ghoo Choi
The electrical losses in power systems are divided into non-technical losses (NTLs) and technical losses (TLs). NTL is more harmful than TL because it includes electricity theft, faulty meters and billing errors. It is one of the major concerns in the po...
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O. V. Ostapchuk,P. Yu. Krasovskyi
Pág. 63 - 65
Description to the basic methods of theft of electric power is given and the developed effective device of protecting from thefts is presented.
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