An Algorithm for Accurate Detection and Correction of Technical and Nontechnical Losses Using Smart Metering

Power losses in electric distribution systems are categorized into technical losses (TL) and nontechnical losses (NTL). TL refer to the heat losses in the distribution system components. NTL, however, refer to losses that come in different shapes and forms, such as tampering with smart meters, attac...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement Vol. 69; no. 11; pp. 8809 - 8820
Main Authors: Shah, Abdullah L., Mesbah, Wessam, Al-Awami, Ali T.
Format: Journal Article
Language:English
Published: New York IEEE 01-11-2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Power losses in electric distribution systems are categorized into technical losses (TL) and nontechnical losses (NTL). TL refer to the heat losses in the distribution system components. NTL, however, refer to losses that come in different shapes and forms, such as tampering with smart meters, attacking the data transmitted from smart meters, malfunctioning of smart meters, and tapping service cables. To accurately detect and correct NTL, it is essential to first estimate the TL. Estimating TL requires knowledge of the network topology and cable impedances, which might not be readily available for the concerned utility company. This article proposes an algorithm with the following functions: remotely characterizing and updating the cable impedances, detecting and classifying the type of losses, estimating the TL and NTL when a smart meter is in error, estimating these losses due to tapping a power cable by a registered or an unregistered user, and estimating these losses due to a cyber-attack. Both active and reactive powers are considered. The proposed algorithm deploys a modified version of the Hamming code, which is originally used in the detection and correction of errors in binary data transmission. Simulation results verify the accuracy and effectiveness of the proposed algorithm.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2020.2999175