dc.contributor
Universitat Politècnica de Catalunya. Doctorat en Enginyeria Elèctrica
dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica
dc.contributor
Universitat Politècnica de Catalunya. CITCEA-UPC - Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments
dc.contributor.author
Jené Vinuesa, Marc
dc.contributor.author
Abdullah, Abdullah
dc.contributor.author
Aragüés Peñalba, Mònica
dc.contributor.author
Sumper, Andreas
dc.identifier
Jené, M. [et al.]. Enhancing fraud detection in renewable energy grids through behind-the-meter PV disaggregation. A: IEEE Innovative Smart Grid Technologies Conference Europe. "IEEE PES ISGT Europe 2024: conference book: ISGT Europe 2024, 14-17 October 2024, Dubrovnik, Croatia". Institute of Electrical and Electronics Engineers (IEEE), 2024, p. 1-5. ISBN 979-8-3503-9042-1. DOI 10.1109/ISGTEUROPE62998.2024.10863072 .
dc.identifier
979-8-3503-9042-1
dc.identifier
https://hdl.handle.net/2117/428542
dc.identifier
10.1109/ISGTEUROPE62998.2024.10863072
dc.description.abstract
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstract
Detecting non-technical losses (NTL) in electrical grids with high renewable energy penetration presents unique challenges. This study proposes a methodology that combines a two-step behind-the-meter (BTM) photovoltaic (PV) disaggregation algorithm with an unsupervised fraud detection model to improve the detection rate in renewable energy grids. The methodology is validated using real-world data from the Ausgrid dataset, comprising several prosumers with BTM PV systems. The disaggregation algorithm accurately estimates the PV capacity with a Mean Average Percentual Error (MAPE) of 7.85%. Applying the disaggregation model improves fraud detection performance, increasing the Matthews Correlation Coefficient (MCC) from 0.654 to 0.747. These services have been developed and tested within the OMEGA-X European project.
dc.description.abstract
Postprint (author's final draft)
dc.format
application/pdf
dc.publisher
Institute of Electrical and Electronics Engineers (IEEE)
dc.relation
https://ieeexplore.ieee.org/abstract/document/10863072
dc.subject
Àrees temàtiques de la UPC::Enginyeria elèctrica
dc.subject
Àrees temàtiques de la UPC::Energies::Recursos energètics renovables
dc.subject
Photovoltaic systems
dc.subject
Correlation coefficient
dc.subject
Renewable energy sources
dc.title
Enhancing fraud detection in renewable energy grids through behind-the-meter PV disaggregation
dc.type
Conference lecture