Work

Anomaly Detection in Low-Voltage Grids with LSTM Autoencoders: A Study on Future Scenario Impacts

Year: 2024

Type: conference-paper

Source: IEEE PES Innovative Smart Grid Technologies Europe

DOI: 10.1109/isgteurope62998.2024.10863300

Authors: Razieh Balouchi Anaraki, Rajkumar Palaniappan, Ulf Häger, Christian Rehtanz

Institution: TU Dortmund University

Language: English

Topic: Electricity Theft Detection Techniques

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: closed

Funder: Projektträger Jülich

OpenAlex ID: W4407363162

FWCI: 0.8

Cites: 13

Cited by: 1

Related to: 10