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Energy Theft Detection via Compressive Sensing Methods


D. Drzajic

Semester Thesis, FS15 (10358)

Advanced Metering Infrastructure (AMI) are being increasingly employed in modern power distribution networks, enabling a new level of pervasive monitoring and, at the same time, opening new vulnerabilities to cyber threats. In this project we focused on the problem of energy theft, and we have developed a monitoring algorithm for the detection of such malicious events. The proposed method is based on compressed sensing techniques which involve solving state-estimation-like problems whose solution is constrained to appropriate types of sparsity (induced by employing different relevant norms). A linearized AC model is adopted for the numerical solution of the estimation problem, and several simulations have been performed to illustrate the performance of the method, showing furthermore valid application also for three-phase models.

Supervisors: Saverio Bolognani, Florian Dörfler


Type of Publication:

(13)Semester/Bachelor Thesis

F. Dörfler

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2015:IFA_5225
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