Model Predictive Control Design for the Secondary Frequency Control of Microgrid Considering Time Delay Attacks

Fast depleting fossil fuels and growing awareness of environmental protection have raised worldwide concerns, aiming to build a sustainable and smart energy ecosystem. Renewable energy generation plays an important role in providing clean power supply. However, the integration of a bulk renewable generation system would also introduce new forms of disturbances and uncertainties to impact the power quality, threatening the secure operation of the distribution network. Microgrid, as an emerging technology, is quite appealing to be interfaced with distribution systems due to its potential economic, environmental, and technical benefits. The microgrid differs from the “smart grid” with different control strategies to accomplish the goal of helping the power grid with load balancing and voltage control and assisting power markets. A hierarchical control structure for the microgrid is commonly designed to address all above issues both in islanded mode and grid-connected mode. On the other hand, concerns about cybersecurity threats in the microgrid are steadily rising, and enormous number of economic losses would occur if defense strategies are not stipulated and carried out. In the modern power system, distributed control system, intelligent measuring devices and Internet of Things (IoT) are highly recommended in microgrid systems, which lead to the vulnerability of communication channels. Cyber threats such as false data injection (FDI) attacks, denial of service (DoS) attacks, and time-delay switch attacks (TDS) can be effortlessly implemented through information and communication centers, compromising the secure operation of power systems. By theoretically analyzing the AC microgrid simulation model, the MPC control strategies, and the modified MPC method based on GCC estimation will be studied in this thesis. In the second chapter, this thesis summarizes the start-art-of microgrid control, introducing a hierarchical control structure: primary control, secondary control, and tertiary control. These control levels differ in their speed of response, the time frame in which they operate, and infrastructure requirements. We focus on the centralized secondary frequency control system, which compensates the frequency deviation caused by primary control—P/f method. Then, in Chapter 3, the isolated AC MG frequency control system including WTG, DEG, PV panel and energy storage system with MPC controller is modeled. Three case studies are designed in MATLAB/Simulink to illustrate the advantages of the MPC method compared with the traditional PI controller. In the next Chapter, since state estimation based on precise status feedback of the system components is essential for the MPC controller to calculate corresponding control signal, the status feedback attack to BESS and FESS is considered. Correspondingly, an online status switching method is proposed to detect the original statuses of BESS and FESS, updating the state estimation function to obtain desirable performance of frequency regulation. Last, considering the time delay attack hacked by the adversary in the sensor, a modified MPC method based on GCC estimation is proposed to detect and track time delay attacks online. The model of proposed method to regulate frequency deviation is built in MATLAB. There are three case studies in this part: a constant time-delay attack with 0.1 pu load increase; a time-varying delay attack with 0.1 pu load increase; and a time-varying delay attack with changing load disturbance. By analyzing results of three cases, the effectiveness of the modified MPC method is proved

Model Predictive Control Design for the Secondary Frequency Control of Microgrid Considering Time Delay Attacks

Fast depleting fossil fuels and growing awareness of environmental protection have raised worldwide concerns, aiming to build a sustainable and smart energy ecosystem. Renewable energy generation plays an important role in providing clean power supply. However, the integration of a bulk renewable generation system would also introduce new forms of disturbances and uncertainties to impact the power quality, threatening the secure operation of the distribution network. Microgrid, as an emerging technology, is quite appealing to be interfaced with distribution systems due to its potential economic, environmental, and technical benefits. The microgrid differs from the “smart grid” with different control strategies to accomplish the goal of helping the power grid with load balancing and voltage control and assisting power markets. A hierarchical control structure for the microgrid is commonly designed to address all above issues both in islanded mode and grid-connected mode. On the other hand, concerns about cybersecurity threats in the microgrid are steadily rising, and enormous number of economic losses would occur if defense strategies are not stipulated and carried out. In the modern power system, distributed control system, intelligent measuring devices and Internet of Things (IoT) are highly recommended in microgrid systems, which lead to the vulnerability of communication channels. Cyber threats such as false data injection (FDI) attacks, denial of service (DoS) attacks, and time-delay switch attacks (TDS) can be effortlessly implemented through information and communication centers, compromising the secure operation of power systems. By theoretically analyzing the AC microgrid simulation model, the MPC control strategies, and the modified MPC method based on GCC estimation will be studied in this thesis. In the second chapter, this thesis summarizes the start-art-of microgrid control, introducing a hierarchical control structure: primary control, secondary control, and tertiary control. These control levels differ in their speed of response, the time frame in which they operate, and infrastructure requirements. We focus on the centralized secondary frequency control system, which compensates the frequency deviation caused by primary control—P/f method. Then, in Chapter 3, the isolated AC MG frequency control system including WTG, DEG, PV panel and energy storage system with MPC controller is modeled. Three case studies are designed in MATLAB/Simulink to illustrate the advantages of the MPC method compared with the traditional PI controller. In the next Chapter, since state estimation based on precise status feedback of the system components is essential for the MPC controller to calculate corresponding control signal, the status feedback attack to BESS and FESS is considered. Correspondingly, an online status switching method is proposed to detect the original statuses of BESS and FESS, updating the state estimation function to obtain desirable performance of frequency regulation. Last, considering the time delay attack hacked by the adversary in the sensor, a modified MPC method based on GCC estimation is proposed to detect and track time delay attacks online. The model of proposed method to regulate frequency deviation is built in MATLAB. There are three case studies in this part: a constant time-delay attack with 0.1 pu load increase; a time-varying delay attack with 0.1 pu load increase; and a time-varying delay attack with changing load disturbance. By analyzing results of three cases, the effectiveness of the modified MPC method is proved

Machine Learning Methods for Attack Detection in the Smart Grid

Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semi-supervised) are employed with decision and feature level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than the attack detection algorithms which employ state vector estimation methods in the proposed attack detection framework.Comment: 14 pages, 11 Figure

Secure Distributed Dynamic State Estimation in Wide-Area Smart Grids

Smart grid is a large complex network with a myriad of vulnerabilities, usually operated in adversarial settings and regulated based on estimated system states. In this study, we propose a novel highly secure distributed dynamic state estimation mechanism for wide-area (multi-area) smart grids, composed of geographically separated subregions, each supervised by a local control center. We firstly propose a distributed state estimator assuming regular system operation, that achieves near-optimal performance based on the local Kalman filters and with the exchange of necessary information between local centers. To enhance the security, we further propose to (i) protect the network database and the network communication channels against attacks and data manipulations via a blockchain (BC)-based system design, where the BC operates on the peer-to-peer network of local centers, (ii) locally detect the measurement anomalies in real-time to eliminate their effects on the state estimation process, and (iii) detect misbehaving (hacked/faulty) local centers in real-time via a distributed trust management scheme over the network. We provide theoretical guarantees regarding the false alarm rates of the proposed detection schemes, where the false alarms can be easily controlled. Numerical studies illustrate that the proposed mechanism offers reliable state estimation under regular system operation, timely and accurate detection of anomalies, and good state recovery performance in case of anomalies

Distributed watermarking for secure control of microgrids under replay attacks

The problem of replay attacks in the communication network between Distributed Generation Units (DGUs) of a DC microgrid is examined. The DGUs are regulated through a hierarchical control architecture, and are networked to achieve secondary control objectives. Following analysis of the detectability of replay attacks by a distributed monitoring scheme previously proposed, the need for a watermarking signal is identified. Hence, conditions are given on the watermark in order to guarantee detection of replay attacks, and such a signal is designed. Simulations are then presented to demonstrate the effectiveness of the technique