TY - GEN
T1 - Identifying security vulnerabilities of weakly detectable network parameter errors
AU - Lin, Yuzhang
AU - Abur, Ali
N1 - Funding Information:
This work was supported in part by the Engineering Research Center Program of the National Science Foundation and the Department of Energy under NSF Award Number EEC-1041877 and the CURENT Industry Partnership Program. Facilities provided by the N-CORE program under Northeastern University’s Global Resilience Institute are also acknowledged.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - This paper is concerned about the security vulnerabilities in the implementation of the Congestion Revenue Rights (CRR) markets. Such problems may be due to the weakly detectable network model parameter errors which are commonly found in power systems. CRRs are financial tools for hedging the risk of congestion charges in power markets. The reimbursements received by CRR holders are determined by the congestion patterns and Locational Marginal Prices (LMPs) in the day-ahead markets, which heavily rely on the parameters in the network model. It is recently shown that detection of errors in certain network model parameters may be very difficult. This paper's primary goal is to illustrate the lack of market security due to such vulnerabilities, i.e. CRR market calculations can be manipulated by injecting parameter errors which are not likely to be detected. A case study using the IEEE 14-bus system will illustrate the feasibility of such undetectable manipulations. Several suggestions for preventing such cyber security issues are provided at the end of the paper.
AB - This paper is concerned about the security vulnerabilities in the implementation of the Congestion Revenue Rights (CRR) markets. Such problems may be due to the weakly detectable network model parameter errors which are commonly found in power systems. CRRs are financial tools for hedging the risk of congestion charges in power markets. The reimbursements received by CRR holders are determined by the congestion patterns and Locational Marginal Prices (LMPs) in the day-ahead markets, which heavily rely on the parameters in the network model. It is recently shown that detection of errors in certain network model parameters may be very difficult. This paper's primary goal is to illustrate the lack of market security due to such vulnerabilities, i.e. CRR market calculations can be manipulated by injecting parameter errors which are not likely to be detected. A case study using the IEEE 14-bus system will illustrate the feasibility of such undetectable manipulations. Several suggestions for preventing such cyber security issues are provided at the end of the paper.
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U2 - 10.1109/ALLERTON.2017.8262751
DO - 10.1109/ALLERTON.2017.8262751
M3 - Conference contribution
AN - SCOPUS:85047932309
T3 - 55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
SP - 295
EP - 301
BT - 55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
Y2 - 3 October 2017 through 6 October 2017
ER -