Abstract
Power losses in the power grid are categorized into technical and non-technical losses (NTL). NTL include attacking the metering unit, attacking the data of the metering system, or meter malfunctions. A report published in 2017 by a smart infrastructure market intelligence firm estimates the global annual losses due to NTL to be 96 billion US dollars. To reduce the NTL in the distribution systems, deploying a robust NTL detection/correction technique is essential. This work provides a hardware demonstration for a novel coding-based metering system that has been proposed in an earlier work for attack detection and correction. It is worth mentioning that a hardware demonstration/verification for the coding-based metering system has not been reported yet in the literature. The coding-based metering system is based on the Hamming code, which was originally used to detect and correct errors in binary data transmission. It can efficiently detect/correct an attack on smart meters using only very few additional meters. The laboratory testing showed the robustness and effectiveness of the coding-based system.
Original language | English |
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Title of host publication | 2022 Saudi Arabia Smart Grid Conference, SASG 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781665475891 |
DOIs | |
State | Published - 2022 |
Event | 2022 Saudi Arabia Smart Grid Conference, SASG 2022 - Jeddah, Saudi Arabia Duration: 12 Dec 2022 → 14 Dec 2022 |
Publication series
Name | 2022 Saudi Arabia Smart Grid Conference, SASG 2022 |
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Conference
Conference | 2022 Saudi Arabia Smart Grid Conference, SASG 2022 |
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Country/Territory | Saudi Arabia |
City | Jeddah |
Period | 12/12/22 → 14/12/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Keywords
- attack detection
- data acquisition
- fraud detection
- hamming code
- non-technical losses (NTL)
- smart metering
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Control and Optimization