Trilevel smart meter hardening strategy for mitigating cyber attacks against Volt/VAR optimization in smart power distribution systems

Daranith Choeum and Dae-Hyun Choi

Applied Energy, 2021, vol. 304, issue C, No S030626192101062X

Abstract: Smart meter data are crucial information for applications in distribution management system (DMS) to manage the distribution system in a reliable and secure manner. However, the smart meter can be attacked by an adversary through the injection of false data into smart meters. This cyber attack can lead to malfunction of the applications that use smart meter data, thereby yielding an abnormal distribution system operation. This paper presents a multilevel optimization-based smart meter hardening strategy where a defender can mitigate the detrimental impact of cyber attacks on volt/VAR optimization (VVO) in DMS via the manipulation of smart meter data. A trilevel defender–attacker–defender (DAD) model with limited attack and defense resources is proposed to determine an optimal attack mitigation strategy. The proposed DAD model aims to identify smart meters that must be hardened from the VVO attack (upper level) while considering both the worst-case attack against the VVO (middle level) and the VVO during the attack (lower level). A nested column-and-constraint generation algorithm is applied to the DAD model to identify and prioritize the most essential smart meters that should be hardened to mitigate the impact of the VVO attack. An IEEE 33-node distribution feeder was used to quantify the performance of the proposed mitigation framework in terms of voltage deviation, solar photovoltaic (PV) penetration level, attack/defense resources, and computational complexity. The simulation results show that mean percentage errors for voltage deviation of the attack and the defense are calculated as 22.02% and 6.22%, respectively.

Keywords: Volt/VAR optimization; Trilevel optimization; Cyber attack; Defender; Smart power distribution system; Smart meter (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030626192101062X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:304:y:2021:i:c:s030626192101062x

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2021.117710

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().