Séminaire au DIC: «Machine Learning for the Detection of Electricity Theft»

Voici l’annonce du 6e séminaire au DIC pour la session HIVER 2018  par Patrick GLAUNER

Titre : Machine Learning for the Detection of Electricity Theft

Résumé

Electricity losses are a frequently appearing problem in power grids. Non-technical losses (NTL) appear during distribution and include, but are not limited to, the following causes: Meter tampering in order to record lower consumptions, bypassing meters by rigging lines from the power source, arranged false meter readings by bribing meter readers and faulty or broken meters. NTL are also reported to range up to 40% of the total electricity distributed in countries such as Brazil, India, Malaysia or Lebanon. This talk will provide an introduction to the detection of NTL using machine learning. Practical case studies on real data sets will be included. This talk will also cover the current research challenges of NTL detection and provide an outreach on how these challenges could be solved in the coming years.

Biographie

Patrick GLAUNER is a PhD student at the University of Luxembourg working on the detection of electricity theft through machine learning. He graduated as valedictorian from Karlsruhe University of Applied Sciences with a BSc in computer science and obtained his MSc in machine learning from Imperial College London. He was a CERN Fellow, worked at SAP and is an alumnus of the German National Academic Foundation (Studienstiftung des deutschen Volkes). He is also adjunct lecturer of artificial intelligence at Karlsruhe University of Applied Sciences. His current interests include anomaly detection, big data, computer vision, deep learning and time series.