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Modeling and evaluation of cyber-attacks on grid-interactive efficient buildings

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  • Fu, Yangyang
  • O'Neill, Zheng
  • Yang, Zhiyao
  • Adetola, Veronica
  • Wen, Jin
  • Ren, Lingyu
  • Wagner, Tim
  • Zhu, Qi
  • Wu, Terresa

Abstract

Grid-interactive efficient buildings (GEBs) are not only exposed to passive threats (e.g., physical faults) but also active threats such as cyber-attacks launched on the network-based control systems. The impact of cyber-attacks on GEB operation are not yet fully understood, especially as regards the performance of grid services. To quantify the consequences of cyber-attacks on GEBs, this paper proposes a modeling and simulation framework that includes different cyber-attack models and key performance indexes to quantify the performance of GEB operation under cyber-attacks. The framework is numerically demonstrated to model and evaluate cyber-attacks such as data intrusion attacks and Denial-of-Service attacks on a typical medium-sized office building that uses the BACnet/IP protocol for communication networks. Simulation results show that, while different types of attacks could compromise the building systems to different extents, attacks via the remote control of a chiller yield the most significant consequences on a building system’s operation, including both the building service and the grid service. It is also noted that a cyber-attack impacts the building systems during the attack period as well as the post-attack period, which suggests that both periods should be considered to fully evaluate the consequences of a cyber-attack.

Suggested Citation

  • Fu, Yangyang & O'Neill, Zheng & Yang, Zhiyao & Adetola, Veronica & Wen, Jin & Ren, Lingyu & Wagner, Tim & Zhu, Qi & Wu, Terresa, 2021. "Modeling and evaluation of cyber-attacks on grid-interactive efficient buildings," Applied Energy, Elsevier, vol. 303(C).
  • Handle: RePEc:eee:appene:v:303:y:2021:i:c:s0306261921010060
    DOI: 10.1016/j.apenergy.2021.117639
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    References listed on IDEAS

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    1. Huang, Yu-Lun & Cárdenas, Alvaro A. & Amin, Saurabh & Lin, Zong-Syun & Tsai, Hsin-Yi & Sastry, Shankar, 2009. "Understanding the physical and economic consequences of attacks on control systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 2(3), pages 73-83.
    2. Tang, Rui & Wang, Shengwei, 2019. "Model predictive control for thermal energy storage and thermal comfort optimization of building demand response in smart grids," Applied Energy, Elsevier, vol. 242(C), pages 873-882.
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    Cited by:

    1. Chen, Zhelun & O’Neill, Zheng & Wen, Jin & Pradhan, Ojas & Yang, Tao & Lu, Xing & Lin, Guanjing & Miyata, Shohei & Lee, Seungjae & Shen, Chou & Chiosa, Roberto & Piscitelli, Marco Savino & Capozzoli, , 2023. "A review of data-driven fault detection and diagnostics for building HVAC systems," Applied Energy, Elsevier, vol. 339(C).
    2. Moudgil, Vipul & Hewage, Kasun & Hussain, Syed Asad & Sadiq, Rehan, 2023. "Integration of IoT in building energy infrastructure: A critical review on challenges and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    3. Ding, Shixing & Gu, Wei & Lu, Shuai & Yu, Ruizhi & Sheng, Lina, 2022. "Cyber-attack against heating system in integrated energy systems: Model and propagation mechanism," Applied Energy, Elsevier, vol. 311(C).
    4. Lin, Wen-Ting & Chen, Guo & Huang, Yuhan, 2022. "Incentive edge-based federated learning for false data injection attack detection on power grid state estimation: A novel mechanism design approach," Applied Energy, Elsevier, vol. 314(C).
    5. Fu, Yangyang & Xu, Shichao & Zhu, Qi & O’Neill, Zheng & Adetola, Veronica, 2023. "How good are learning-based control v.s. model-based control for load shifting? Investigations on a single zone building energy system," Energy, Elsevier, vol. 273(C).

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