TY - GEN
T1 - Cyber Attacks on Distributed Congestion Management Methods
AU - Khan, Omniyah Gul M.
AU - El-Saadany, Ehab
AU - Saleh, Khaled
AU - Shaaban, Mostafa
AU - Youssef, Amr
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - With the increased dependency on Demand Side Management (DSM) for congestion mitigation in the distribution network (DN), cyber physical security of such congestion management methods need to be investigated. DSM based distributed congestion management methods rely on the aggregators' communication of consumers load profiles to the distribution network operator (DNO). Compromising the aggregator would hence affect the congestion management results. To gain insights into the vulnerability of such congestion management methods, different cyber attack scenarios are studied in this paper assuming a compromised aggregator. Simulation results, based on the IEEE 33 bus system, show how the electricity prices can be manipulated by attacks that increase the load profiles faking congestion. On the other hand, a multiplicative attack that decreases an aggregator's load profile would cause the concealment of congestions when in reality the line is overloaded. These results demonstrate the vulnerability of such congestion management methods to cyber attacks.
AB - With the increased dependency on Demand Side Management (DSM) for congestion mitigation in the distribution network (DN), cyber physical security of such congestion management methods need to be investigated. DSM based distributed congestion management methods rely on the aggregators' communication of consumers load profiles to the distribution network operator (DNO). Compromising the aggregator would hence affect the congestion management results. To gain insights into the vulnerability of such congestion management methods, different cyber attack scenarios are studied in this paper assuming a compromised aggregator. Simulation results, based on the IEEE 33 bus system, show how the electricity prices can be manipulated by attacks that increase the load profiles faking congestion. On the other hand, a multiplicative attack that decreases an aggregator's load profile would cause the concealment of congestions when in reality the line is overloaded. These results demonstrate the vulnerability of such congestion management methods to cyber attacks.
UR - http://www.scopus.com/inward/record.url?scp=85079071670&partnerID=8YFLogxK
U2 - 10.1109/PESGM40551.2019.8973458
DO - 10.1109/PESGM40551.2019.8973458
M3 - Conference contribution
AN - SCOPUS:85079071670
T3 - IEEE Power and Energy Society General Meeting
BT - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019
PB - IEEE Computer Society
T2 - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Y2 - 4 August 2019 through 8 August 2019
ER -