Visible to the public Identifying security vulnerabilities of weakly detectable network parameter errors

TitleIdentifying security vulnerabilities of weakly detectable network parameter errors
Publication TypeConference Paper
Year of Publication2017
AuthorsLin, Y., Abur, A.
Conference Name2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
Keywordscompositionality, congestion charges, congestion patterns, Congestion Revenue Rights markets, CRR holders, CRR market calculations, cyber security issues, day-ahead markets, financial tools, gaussian distribution, Human Behavior, IEEE 14-bus system, LMP, Load flow, locational marginal prices, market security, measurement uncertainty, Metrics, network model parameters, power generation, power markets, power system economics, Power systems, Pricing, pubcrawl, Real-time Systems, Resiliency, security, security vulnerabilities identification, vulnerability detection, weakly detectable network model parameter errors, weakly detectable network parameter errors
AbstractThis 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.
Citation Keylin_identifying_2017