A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

References

• ASHRAE. 2018. 36: High performance sequences of operation for HVAC systems. Atlanta: American Society of Heating, Refrigerating and Air-Conditioning Engineers.
   Google Scholar
• Blum, D., J. Arroyo, S. Huang, J. Drgoňa, F. Jorissen, H. T. Walnum, Y. Chen, K. Benne, D. Vrabie, M. Wetter, et al. 2021. Building optimization testing framework (BOPTEST) for simulation-based benchmarking of control strategies in buildings. Journal of Building Performance Simulation 14 (5):586–610. doi:10.1080/19401493.2021.1986574
   Web of Science ®Google Scholar
• Bushby, S. T., M. A. Galler, N. Milesi Ferretti, and C. Park. 2010. The virtual cybernetic building testbed–A building emulator. ASHRAE Transactions 116 (1):37–44.
   Google Scholar
• Calfa, C., Z. Yang, Y. Li, Z. Chen, Z. O’Neill, and J. Wen. 2023. Performance assessment of a real water source heat pump within a hardware-in-the-loop (HIL) testing environment. Science and Technology for the Built Environment 29 (10):1011–26. doi:10.1080/23744731.2023.2261810
   Web of Science ®Google Scholar
• Chen, Y., Z. Chen, P. Xu, W. Li, H. Sha, Z. Yang, G. Li, and C. Hu. 2019. Quantification of electricity flexibility in demand response: Office building case study. Energy 188:116054. doi:10.1016/j.energy.2019.116054
   Web of Science ®Google Scholar
• Crawley, D. B., L. K. Lawrie, F. C. Winkelmann, W. F. Buhl, Y. Huang, C. O. Pedersen, R. K. Strand, R. J. Liesen, D. E. Fisher, M. J. Witte, et al. 2001. EnergyPlus: Creating a new-generation building energy simulation program. Energy and Buildings 33 (4):319–31. doi:10.1016/S0378-7788(00)00114-6
   Web of Science ®Google Scholar
• Fathy, H. K., Z. S. Filipi, J. Hagena, and J. L. Stein. 2006. Review of hardware-in-the-loop simulation and its prospects in the automotive area. Paper presented at the Modeling and Simulation for Military Applications. doi:10.1117/12.667794
   Google Scholar
• Fritzson, P. 2014. Principles of object-oriented modeling and simulation with Modelica 3.3: A cyber-physical approach. Hoboken, NJ: John Wiley & Sons. doi:10.1002/9781118989166
   Google Scholar
• Fu, Y., Z. O’Neill, and V. Adetola. 2021a. A flexible and generic functional mock-up unit based threat injection framework for grid-interactive efficient buildings: A case study in Modelica. Energy and Buildings 250:111263. doi:10.1016/j.enbuild.2021.111263
   Web of Science ®Google Scholar
• Fu, Y., Z. O’Neill, Z. Yang, V. Adetola, J. Wen, L. Ren, T. Wagner, Q. Zhu, and T. Wu. 2021b. Modeling and evaluation of cyber-attacks on grid-interactive efficient buildings. Applied Energy 303:117639. doi:10.1016/j.apenergy.2021.117639
   Web of Science ®Google Scholar
• Goel, S., M. Rosenberg, R. Athalye, Y. Xie, W. Wang, R. Hart, J. Zhang, and V. Mendon. 2014. Enhancements to ASHRAE standard 90.1 prototype building models. Richland, WA: Pacific Northwest National Lab (PNNL).
   Google Scholar
• Gunes, V., S. Peter, and T. Givargis. 2015. Improving energy efficiency and thermal comfort of smart buildings with HVAC systems in the presence of sensor faults. Paper presented at the 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems.
   Google Scholar
• Holmberg, D. G., and D. Evans. 2003. BACnet wide area network security threat assessment. Gaithersburg, MD: US Department of Commerce, National Institute of Standards and Technology.
   Google Scholar
• Honorof, M. 2013. “Building Hack Almost Landed Google in Hot Water.” https://www.nbcnews.com/id/wbna51805522.
   Google Scholar
• Huang, Y.-L., A. A. Cárdenas, S. Amin, Z.-S. Lin, H.-Y. Tsai, and S. Sastry. 2009. Understanding the physical and economic consequences of attacks on control systems. International Journal of Critical Infrastructure Protection 2 (3):73–83. doi:10.1016/j.ijcip.2009.06.001
   Web of Science ®Google Scholar
• Huang, S., W. Wang, M. R. Brambley, S. Goyal, and W. Zuo. 2018. An agent-based hardware-in-the-loop simulation framework for building controls. Energy and Buildings 181:26–37. doi:10.1016/j.enbuild.2018.09.038
   Web of Science ®Google Scholar
• Isermann, R., J. Schaffnit, and S. Sinsel. 1999. Hardware-in-the-loop simulation for the design and testing of engine-control systems. Control Engineering Practice 7 (5):643–53. doi:10.1016/S0967-0661(98)00205-6
   Web of Science ®Google Scholar
• Kaur, J., J. Tonejc, S. Wendzel, and M. Meier. 2015. Securing BACnet’s pitfalls. Paper presented at the IFIP International Information Security and Privacy Conference.
   Google Scholar
• Knospe, C. 2006. PID control. IEEE Control Systems Magazine, 26 (1):30–31.
   Web of Science ®Google Scholar
• Li, G., L. Ren, Y. Fu, Z. Yang, V. Adetola, J. Wen, Q. Zhu, T. Wu, K. Candan, and Z. O'Neill. 2023. A critical review of cyber-physical security for building automation systems. Annual Reviews in Control 55:237–54. doi:10.1016/j.arcontrol.2023.02.004.
   Web of Science ®Google Scholar
• Li, G., Z. Yang, Y. Fu, L. Ren, Z. O'Neill, and C. Parikh. 2022. Development of a hardware-In-the-Loop (HIL) testbed for cyber-physical security in smart buildings. arXiv preprint arXiv:2210.11234.
   Google Scholar
• Li, G., Y. Fu, A. Pertzborn, J. Wen, and Z. O’neill. 2021. An ice storage tank modelica model: Implementation and validation. Paper presented at the Modelica Conferences.
   Google Scholar
• Li, G., Y. Fu, A. Pertzborn, Z. O’Neill, and J. Wen. 2022. Demand flexibility evaluation for building energy systems with active thermal storage using model predictive control. Paper presented at the 2022 ASHRAE Annual Conference, Toronto, Canada.
   Google Scholar
• Li, G., Z. O'Neill, J. Wen, O. Pradhan, L. Ren, T. Wu, V. Adetola, K. S. Candan, and Q. Zhu. 2023. CYDRES: CYber Defense and REsilient System for securing grid-interactive efficient buildings. Paper presented at the Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. doi:10.1145/3600100.3626273
   Google Scholar
• Lou, X., C. Tran, R. Tan, D. K. Y. Yau, and Z. T. Kalbarczyk. 2019. Assessing and mitigating impact of time delay attack: A case study for power grid frequency control. Paper presented at the. Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems.
   Google Scholar
• Lu, X., Y. Fu, Z. O'Neill, and J. Wen. 2021. A holistic fault impact analysis of the high-performance sequences of operation for HVAC systems: Modelica-based case study in a medium-office building. Energy and Buildings 252:111448. doi:10.1016/j.enbuild.2021.111448
   Web of Science ®Google Scholar
• O’Neill, Z., and A. Henry. 2016. Development of a Hardware-in-the-loop Framework with Modelica for Energy Efficient Buildings. Paper presented at the Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments.
   Google Scholar
• Otten, R., B. Li, and A. Alleyne. 2010. Hardware-in-the-loop load emulation for air-conditioning and refrigeration systems.
   Google Scholar
• Paridari, K., N. O'Mahony, A. El-Din Mady, R. Chabukswar, M. Boubekeur, and H. Sandberg. 2018. A framework for attack-resilient industrial control systems: Attack detection and controller reconfiguration. Proceedings of the IEEE 106 (1):113–28. doi:10.1109/JPROC.2017.2725482
   Web of Science ®Google Scholar
• Peacock, M. 2019. Anomaly detection in BACnet/IP managed building automation systems.
   Google Scholar
• Roth, A., and J. Reyna. 2019. Grid-interactive efficient buildings technical report series: Whole-building controls, sensors, modeling, and analytics. USDOE Office of Energy Efficiency and Renewable Energy (EERE).
   Google Scholar
• Seem, J. E. 1998. A new pattern recognition adaptive controller with application to HVAC systems. Automatica 34 (8):969–82. doi:10.1016/S0005-1098(98)00033-8
   Web of Science ®Google Scholar
• Sridhar, S., and M. Govindarasu. 2014. Model-based attack detection and mitigation for automatic generation control. IEEE Transactions on Smart Grid 5 (2):580–91. doi:10.1109/TSG.2014.2298195
   Web of Science ®Google Scholar
• Sridhar, S., and G. Manimaran. 2010. Data integrity attacks and their impacts on SCADA control system. Paper presented at the IEEE PES General Meeting.
   Google Scholar
• Taylor, S. 2020. Advanced sequences of operation for HVAC systems-phase II central plants and hydronic systems. ASHRAE RP-1711 (in progress).
   Google Scholar
• U.S. Department of Energy (DOE). 2015. Chapter 5: Increasing efficiency of building systems and technologies. In Quadrennial technology review: An assessment of energy technologies and research opportunities, 143–81. https://www.energy.gov/quadrennial-technology-review-2015
   Google Scholar
• Vijayan, J. 2014. Target attack shows danger of remotely accessible HVAC systems. https://www.computerworld.com/article/2487452/target-attack-shows-danger-of-remotely-accessible-hvac-systems.html.
   Google Scholar
• Wardell, D. C., R. F. Mills, G. L. Peterson, and M. E. Oxley. 2016. A method for revealing and addressing security vulnerabilities in cyber-physical systems by modeling malicious agent interactions with formal verification. Procedia Computer Science 95:24–31. doi:10.1016/j.procs.2016.09.289
   Google Scholar
• Werth, A. W., and T. H. Morris. 2021. Prototyping PLCs and IoT devices in an HVAC virtual testbed to study impacts of cyberattacks. Paper presented at the Proceedings of Fifth International Congress on Information and Communication Technology: ICICT 2020, London.
   Google Scholar
• Wetter, M., W. Zuo, T. S. Nouidui, and X. Pang. 2014. Modelica buildings library. Journal of Building Performance Simulation 7 (4):253–70. doi:10.1080/19401493.2013.765506
   Web of Science ®Google Scholar
• Xu, P., P. Haves, and J. Deringer. 2004. A simulation-based testing and training environment for building controls.
   Google Scholar
• Zhang, Y., S. Eisele, A. Dubey, A. Laszka, and A. K. Srivastava. 2019. Cyber-physical simulation platform for security assessment of transactive energy systems. Paper presented at the 2019 7th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES). doi:10.1109/MSCPES.2019.8738802
   Google Scholar
• Zhao, Y., T. Li, X. Zhang, and C. Zhang. 2019. Artificial intelligence-based fault detection and diagnosis methods for building energy systems: Advantages, challenges and the future. Renewable and Sustainable Energy Reviews 109:85–101. doi:10.1016/j.rser.2019.04.021
   Web of Science ®Google Scholar
• Zhao, F., J. Fan, and S. Mijanovic. 2013. PI auto-tuning and performance assessment in HVAC systems. Paper presented at the 2013 American Control Conference.
   Google Scholar