Dr. Guanyu Tian

Grid-interactive buildings are increasingly crucial in smart grid demand response (DR) programs due to their power flexibility, mainly from the thermal inertia of the heating, ventilation, and air conditioning (HVAC) systems. Thus, adjusting the HVAC system to desired power while maintaining a preferred room temperature is critical for building managers and system operators. In this presentation, we focus on the power tracking of HVAC systems under DR programs when faced with cyber-attacks on IoT sensors. This issue is divided into two levels. At a higher level, we identify the appropriate HVAC system setpoints that yield the desired power consumption. We propose a semidefinite programming (SDP) based quantification method to construct the flexibility table that provides guidance on HVAC setpoint adjustment. The SDP reformulates the non-convex problem of HVAC power optimization, and can be solved efficiently in real-time. The physics-based HVAC model guarantees the reliability and accuracy of solutions. The obtained response strategies can minimize occupant discomfort while meeting grid power requirements.

However, cyber-attacks that alter sensor values can undermine the accuracy and flexibility of HVAC system power adjustment. Hence, in the lower level, we propose a stochastic optimization-based stealthy sensor attack method and a corresponding defense strategy: a resilient control framework. We test these methods using digital twin models of a test building with a single-chiller HVAC system. Simulation results demonstrate that minor falsifications caused by a stealthy sensor attack can significantly alter the power profile, leading to large power tracking errors. However, the resilient control framework can reduce the power tracking error by over 60\% under such attacks without filtering out compromised data.

Biography:

Guanyu Tian received his Ph.D. from the University of Central Florida in 2022. Before that he earned his B.S. in Electrical Engineering from Shandong University, Jinan, China in 2015 and M.S. from Rensselaer Polytechnic Institute, Troy, NY, USA in 2016. He is currently a post-doctoral scholar at the Smart Infrastructure Data Analytics Laboratory at UCF. His research focuses on the study of grid-interactive buildings, including the aspects of modeling, autonomous control, and cyber-security.

Dr. Mazhar Ali

Cyber-physical systems (CPS) refer to the next generation of systems that integrate communication, computation, and control to enable more reliable, efficient, and robust physical systems’ operation. The CPS framework serves as the foundation for the modern architecture of critical infrastructures, including electrical power grids, oil and natural gas distribution, transportation systems, and many more. Although the CPS design has assisted in the reliable, efficient, and robust service of physical systems, it has also raised tremendous concern about secure and resilient operation due to the coupling and the presence of several hardware and software products among different CPS layers. These vulnerabilities have opened up a new avenue for adversaries to deploy coordinated cyber-physical attacks, with difficult detection, isolation, and recovery of the CPS. In our research, we explore new types of coordinated cyber-physical attacks, such as multistage and multiwave. Multistage attacks represent a distinct type of attack in which numerous stages are involved, and the attack at the present stage is coupled with the successful completion of the attack at the prior stage. An example of a multistage attack is the one that occurred in 2015 against the Ukrainian power grid. In contrast to multistage, multiwave CPS attacks are unique spatial and temporal coordinated attacks. In these attacks, the adversaries tactically breach the cyber system and choose particular devices in cyber/physical systems to launch consecutive attacks at various time steps. To address the challenges arising from the coordinated attacks, we have developed a general model for multistage and multiwave attacks with adaptive restoration techniques and restoration strategy metrics to ensure secure and resilient operation and recovery from these coordinated cyber-physical attacks. We are also developing a CPS testbed for validation and demonstration. The proposed solutions from our research work could be equally applicable to other CPS.

Biography:

Dr. Ali received his B.Sc. in Mechanical Engineering from the University of Lahore, Lahore, Pakistan. He received M.Sc. and Ph.D. from the Skolkovo Institute of Science and Technology, Moscow, Russia, in 2015 and 2019, respectively. Dr. Ali was also an exchange/visiting student at the Massachusetts Institute of Technology, USA. Dr. Ali is currently working as a Postdoc at the University of Central Florida, Department of Electrical Engineering & Computer Science. His research is focused on voltage stability, power-flow solution space, computational methods, mathematical optimization, and secure & resilient operations of Cyber Physical-Systems.