| 1. |
- Björk, Joakim, 1989-
(författare)
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Fundamental Control Performance Limitations for Interarea Oscillation Damping and Frequency Stability
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With the transition towards renewable energy and the deregulation of the electricity markets, the power system is changing. Growing electricity demand and more intermittent power production increase the need for transfer capacity. Lower inertia levels due to a higher share of renewables increase the need for fast frequency reserves (FFR). In this thesis, we study fundamental control limitations for improving the damping of interarea oscillations and frequency stability.The first part of the thesis considers the damping of oscillatory interarea modes. These system-wide modes involve power oscillating between groups of generators and are sometimes hard to control due to their scale and complexity. We consider limitations of decentralized control schemes based on local measurements, as well as centralized control schemes with limitations associated to actuator dynamics and network topology. It is shown that the stability of asynchronous grids can be improved by modulating the active power of a single interconnecting high-voltage direct current (HVDC) link. One challenge with modulating HVDC active power is that the interaction between interarea modes of the two grids may have a negative impact on system stability. By studying the controllability Gramian, we show that it is possible to improve the damping in both grids as long as the frequencies of their interarea modes are not too close. It is demonstrated how the controllability, and therefore the achievable damping, deteriorates as the frequency difference becomes small. With a modal frequency difference of 5%, the damping can be improved by around 2 percentage points whereas a modal frequency difference of 20% allows for around 8 percentage points damping improvement. The results are validated by simulating two HVDC-interconnected 32-bus power system models. We also consider the coordinated control of two and more HVDC links. For some network configurations, it is shown that the interaction between troublesome interarea modes can be avoided. The second part considers the coordination of frequency containment reserves (FCR) in low-inertia power systems. A case study is performed in a 5-machine model of the Nordic synchronous grid. We consider a low-inertia test case where FCR are provided by hydro power. The non-minimum phase characteristic of the waterways limits the achievable bandwidth of the FCR control. It is shown that a consequence of this is that hydro-FCR fails at keeping the frequency nadir above the 49.0 Hz safety limit following the loss of a HVDC link that imports 1400 MW. To improve the dynamic frequency stability, FFR from wind power is considered. For this, a new wind turbine model is developed. The turbine is controlled at variable-speed, enabling FFR by temporarily borrowing energy from the rotating turbine. The nonlinear wind turbine dynamics are linearized to facilitate a control design that coordinate FFR from the wind with slow FCR from hydropower. Complementary wind resources with a total rating of 2000 MW, operating at 70–90% rated wind speeds, is shown to be more than enough to fulfill the frequency stability requirements. The nadir is kept above 49.0 Hz without the need to install battery storage or to waste wind energy by curtailing the wind turbines.
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| 2. |
- Liu, Hanxiao, 1995-
(författare)
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Analysis, Detection, and Mitigation of Attacks in Cyber-physical Systems
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cyber-Physical Systems (CPS) offer close integration among computational elements, communication networks, and physical processes. Such systems play an increasingly important role in a large variety of fields, such as manufacturing, health care, environment, transportation, defence, and so on. Due to the wide applications and critical functions of CPS, increasing importance has been attached to their security. In this thesis, we focus on the security of CPS by investigating vulnerability under cyber-attacks, providing detection mechanisms, and developing feasible countermeasures against cyber-attacks.The first contribution of this thesis is to analyze the performance of remote state estimation under linear attacks. A linear time-invariant system equipped with a smart sensor is studied. The adversary aims to maximize the state estimation error covariance while staying stealthy. The maximal performance degradation that an adversary can achieve with any linear first-order false data injection attack under strict stealthiness for vector systems and $\epsilon$-stealthiness for scalar systems is characterized. We also provide an explicit attack strategy that achieves this bound and compare it with strategies previously proposed in the literature. The second problem of this thesis is about the detection of replay attacks. We aim to design physical watermark signals and corresponding detector to protect a control system against replay attacks. For a scenario where the system parameters are available to the operator, a physical watermarking scheme to detect the replay attack is introduced. The optimal watermark signal design problem is formulated as an optimization problem, and the optimal watermark signal and detector are derived. Subsequently, for systems with unknown parameters, we provide an on-line learning mechanism to asymptotically derive the optimal watermarking signal and corresponding detector.The third problem under investigation is about the detection of false-data injection attacks when the attacker injects malicious data to flip the distribution of the manipulated sensor measurements. The detector decides to continue taking observations or to stop based on the received signals, and the goal is to have the flip attack detected as fast as possible while trying to avoid terminating the measurements when no attack is present. The detection problem is modeled as a partially observable Markov decision process (POMDP) by assuming an attack probability, with the dynamics of the hidden states of the POMDP characterized by a stochastic shortest path (SSP) problem. The optimal policy of the SSP solely depends on the transition costs and is independent of the assumed attack probability. By using a fixed-length window and suitable feature function of the measurements, a Markov decision process (MDP) is used to approximate the POMDP. The optimal solution of the MDP is obtained by reinforcement learning. The fourth contribution of this thesis is to develop a sensor scheduler for remote state estimation under integrity attacks. We seek a trade-off between the energy consumption of communications and accuracy of state estimation when the acknowledgment (ACK) information, sent by the remote estimator to the local sensor, is compromised. The sensor scheduling problem is formulated as an infinite horizon discounted optimal control problem with infinite states. We first analyze the underlying MDP and show that the optimal schedule without ACK attack is of threshold type. Thus, we can simplify the problem by replacing the original state space with a finite state space. For the simplified MDP, when ACK is under attack, the problem is modelled as a POMDP. We analyze the induced MDP that uses a belief vector as its state for the POMDP. The properties of the exact optimal solution are studied via contractive models and it is shown that the threshold solution for the POMDP cannot be readily obtained. A suboptimal solution is provided instead via a rollout approach based on reinforcement learning. We present two variants of rollout and provide corresponding performance bounds.
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| 3. |
- Alisic, Rijad, 1994-
(författare)
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Privacy of Sudden Events in Cyber-Physical Systems
- 2021
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cyberattacks against critical infrastructures has been a growing problem for the past couple of years. These infrastructures are a particularly desirable target for adversaries, due to their vital importance in society. For instance, a stop in the operation of a critical infrastructure could result in a crippling effect on a nation's economy, security or public health. The reason behind this increase is that critical infrastructures have become more complex, often being integrated with a large network of various cyber components. It is through these cyber components that an adversary is able to access the system and conduct their attacks.In this thesis, we consider methods which can be used as a first line of defence against such attacks for Cyber-Physical Systems (CPS). Specifically, we start by studying how information leaks about a system's dynamics helps an adversary to generate attacks that are difficult to detect. In many cases, such attacks can be detrimental to a CPS since they can drive the system to a breaking point without being detected by the operator that is tasked to secure the system. We show that an adversary can use small amounts of data procured from information leaks to generate these undetectable attacks. In particular, we provide the minimal amount of information that is needed in order to keep the attack hidden even if the operator tries to probe the system for attacks. We design defence mechanisms against such information leaks using the Hammersley-Chapman-Robbins lower bound. With it, we study how information leakage could be mitigated through corruption of the data by injection of measurement noise. Specifically, we investigate how information about structured input sequences, which we call events, can be obtained through the output of a dynamical system and how this leakage depends on the system dynamics. For example, it is shown that a system with fast dynamical modes tends to disclose more information about an event compared to a system with slower modes. However, a slower system leaks information over a longer time horizon, which means that an adversary who starts to collect information long after the event has occured might still be able to estimate it. Additionally, we show how sensor placements can affect the information leak. These results are then used to aid the operator to detect privacy vulnerabilities in the design of a CPS.Based on the Hammersley-Chapman-Robbins lower bound, we provide additional defensive mechanisms that can be deployed by an operator online to minimize information leakage. For instance, we propose a method to modify the structured inputs in order to maximize the usage of the existing noise in the system. This mechanism allows us to explicitly deal with the privacy-utility trade-off, which is of interest when optimal control problems are considered. Finally, we show how the adversary's certainty of the event increases as a function of the number of samples they collect. For instance, we provide sufficient conditions for when their estimation variance starts to converge to its final value. This information can be used by an operator to estimate when possible attacks from an adversary could occur, and change the CPS before that, rendering the adversary's collected information useless.
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| 4. |
- Iwaki, Takuya, 1986-
(författare)
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Resource-aware Wireless Process Control
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- To tackle the ever-growing demands on high-quality and cost-effective industrial production, recent developments in embedded sensing, wireless communication, and cloud computing offer great opportunities. Resource-aware reliable wireless communication and real-time control are needed to leverage these technologies. The thesis develops a new design framework for such wireless process control systems. In the first part, an energy-aware multi-hop network scheduler for remote estimation and control is developed. Multiple sensors transmit their data to a remote estimator or controller through a shared multi-hop network. We develop scheduling algorithms determining which links of the network that should be activated and when to convey sensor data. For remote estimation, an optimization problem minimizing a linear combination of the averaged estimation error and network energy is formulated. We solve the problem by splitting it into tree planning and sensor selection subproblems, and show that an optimal periodic schedule can be obtained. The setting is then extended to an optimal control formulation, where an optimal solution minimizes the combination of the averaged linear quadratic Gaussian control cost and network energy consumption. Algorithms to reconfigure schedules and routes when network link outages are present are also introduced. The applicability of the proposed scheduler is demonstrated in numerical examples. In the second part, event-triggered sensing, actuation, and control reconfiguration algorithms are developed. We derive stability conditions under event-triggered actuation for PID, cascade, decoupling, and delay-compensating control systems. Sensors sample and transmit their measurements periodically, while control commands are updated only when a certain event threshold is crossed. A tuning method for the threshold is proposed. We show that the approach yields setpoint tracking and disturbance rejection. Event-triggered sensing together with control reconfiguration is then considered for feedforward and cascade control, illustrating how wireless sensing can efficiently attenuate disturbances. Numerical examples demonstrate how the methods reduce information exchange without closed-loop performance degradation.
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