Work

Anomaly detection and classification in power system state estimation: Combining model-based and data-driven methods

Year: 2023

Type: article

Source: Sustainable Energy Grids and Networks

DOI: 10.1016/j.segan.2023.101116

Authors: Sajjad Asefi, Mile Mitrovic, Dragan Ćetenović, Victor Levi, Elena Gryazina, Vladimir Terzija

Institutions: Tallinn University of Technology, Skolkovo Institute of Science and Technology, University of Kragujevac, University of Manchester

Language: English

Topic: Power System Optimization and Stability

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

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

Open Access status: green

Funders: Ministry of Education and Science of the Russian Federation, Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, Skolkovo Institute of Science and Technology, Engineering and Physical Sciences Research Council

Awards: G1200716830, G1355563978, Supergen Energy Networks hub 2018, G1576455285, Multi-energy Control of Cyber-Physical Urban Energy Systems (MC2), G2574952283, G2694529125, G2919793022, G2976905672, G3104528315, G4588624729, G4870918993, G5238344413, G6650890290, G8655288378

OpenAlex ID: W4385190863

FWCI: 2.485

Cites: 55

Cited by: 34

Related to: 10