Identifying Security Vulnerabilities in Electricity Market Operations Induced by Weakly Detectable Network Parameter Errors

Yuzhang Lin, Ali Abur, Hanchen Xu

Research output: Contribution to journalArticlepeer-review

Abstract

In this article, a new security vulnerability in electricity market operations is identified. It involves certain parameters in the network model database whose errors, by nature, are difficult to detect and identify. These errors can either occur due to unintentional reasons or be maliciously introduced by cyber-adversaries. It is shown that by impacting the injection shift factors and transmission line congestion patterns, these errors may exert biases on locational marginal prices (LMPs), and thus impact the revenues received by the holders of financial transmission rights (FTRs). A method is then developed for identifying the network parameters whose errors are difficult to detect and may have severe impacts on the LMPs and FTR revenues. Simulation results in the IEEE 57-bus system are presented to illustrate and verify the analysis and the proposed method. The proposed framework can be used to conduct cyber-vulnerability assessment for power system model databases.

Original languageEnglish (US)
Article number9134954
Pages (from-to)627-636
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume17
Issue number1
DOIs
StatePublished - Jan 2021

Keywords

  • Anomaly detection
  • cybersecurity
  • electricity market
  • financial transmission right (FTR)
  • locational marginal price (LMP)
  • parameter estimation
  • state estimation (SE)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering

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