Conference paper
The Cyber Security of Battery Energy Storage Systems and Adoption of Data-driven Methods
Battery energy storage systems (BESSs) are becoming a crucial part of electric grids due to their important roles in renewable energy sources (RES) integration in energy systems. Cyber-secure operation of BESS in renewable energy systems is significant, since it is susceptible to cyber threats and its potential failure may result in economical and physical damage to both the BESS and the system.
However, there is a lack of comprehensive study on the attack detection methods for industrial BESSs. This paper reviews the state-of-the-art work in the area of BESS cyber threats, investigates how to detect cyberattackes in the operation stage. We address the problem of enhancing the communication channels' integrity can by implementing blockchain in the design stage of BESS, combined with applying artificial intelligence (AI) and machine learning (ML) methods for false data injection attack (FDIA) detection in the BESS operation stage.
The focus is on the application of ML and AI methods for FDIA detection on different system layers. Based on our analysis, data-driven approaches such as clustering and artificial-neutral-networkbased state estimation (SE) forecast are recommended for the implementation in BESSs.
Language: | English |
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Publisher: | IEEE |
Year: | 2021 |
Pages: | 188-192 |
Proceedings: | 2020 IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering |
ISBN: | 1728187087 , 1728187095 , 9781728187082 and 9781728187099 |
Types: | Conference paper |
DOI: | 10.1109/AIKE48582.2020.00037 |
ORCIDs: | Hashemi Toghroljerdi, Seyedmostafa and Træholt, Chresten |
Artificial intelligence Battery energy storage system Battery state estimation Cyber security Cyber threat Cyberattack False data injection attack Machine learning Renewable energy source SDG 7 - Affordable and Clean Energy
Batteries Electric potential Knowledge engineering Renewable energy sources State estimation State of charge artificial intelligence battery energy storage system battery state estimation cyber security cyber threat cyberattack false data injection attack machine learning renewable energy source