Analysis of end-to-end delay characteristics among various packet sizes in modern substation communication systems based on IEC 61850

Substation plays an important part for electricity generation, transmission and distribution systems, where voltage is stepped up/down or vice versa. The substation serves as a center point of all kind of connection between various power system networks, such as distribution line from electricity generation to household or industrial consumers. Hence, the performance of the substation should be maintained at all times with proper implementation of substation communication systems. A reliable substation communication system relies on the performance of data transmission’s end-to-end delay characteristics in the substation communication systems. In this paper, we modelled, simulated and compared the end-to-end delay characteristics among different data packet sizes as well as different types of substation network topologies using IEC 61850. The simulation results confirmed that the larger packet sizes have higher amount of delays compare to the smaller packet sizes. Besides that, communication network topology with higher number of components obtained the results with a higher amount of end-to-end delays. Therefore, based on the simulated results, it is recommended to reduce the end-to-end delay of substation communication’s data flow for a sustainable and reliable modern power system

Ensemble Feature Learning-Based Event Classification for Cyber-Physical Security of the Smart Grid

The power grids are transforming into the cyber-physical smart grid with increasing two-way communications and abundant data flows. Despite the efficiency and reliability promised by this transformation, the growing threats and incidences of cyber attacks targeting the physical power systems have exposed severe vulnerabilities. To tackle such vulnerabilities, intrusion detection systems (IDS) are proposed to monitor threats for the cyber-physical security of electrical power and energy systems in the smart grid with increasing machine-to-machine communication. However, the multi-sourced, correlated, and often noise-contained data, which record various concurring cyber and physical events, are posing significant challenges to the accurate distinction by IDS among events of inadvertent and malignant natures. Hence, in this research, an ensemble learning-based feature learning and classification for cyber-physical smart grid are designed and implemented. The contribution of this research are (i) the design, implementation and evaluation of an ensemble learning-based attack classifier using extreme gradient boosting (XGBoost) to effectively detect and identify attack threats from the heterogeneous cyber-physical information in the smart grid; (ii) the design, implementation and evaluation of stacked denoising autoencoder (SDAE) to extract highlyrepresentative feature space that allow reconstruction of a noise-free input from noise-corrupted perturbations; (iii) the design, implementation and evaluation of a novel ensemble learning-based feature extractors that combine multiple autoencoder (AE) feature extractors and random forest base classifiers, so as to enable accurate reconstruction of each feature and reliable classification against malicious events. The simulation results validate the usefulness of ensemble learning approach in detecting malicious events in the cyber-physical smart grid

Analysis And Mitigation Of The Impacts Of Delays In Control Of Power Systems With Renewable Energy Sources

ABSTRACT Analysis and Mitigation of the Impacts of Delays in Control of Power Systems with Renewable Energy Sources by Chang Fu Apr. 2019 Advisor : Dr. Caisheng Wang Major : Electrical and Computer Engineering Degree : Doctor of Philosophy With the integration of renewable resources, electric vehicles and other uncertain resources into power grid, varieties of control topology and algorithms have been proposed to increase the stability and reliability of the operation system. Load modeling is an critical part in such analysis since it significantly impacts the accuracy of the simulation in power system, as well as stability and reliability analysis. Traditional power system composite load model parameter identification problems can be essentially ascribed to optimization problems, and the identied parameters are point estimations subject to dierent constraints. These conventional point estimation based composite load modeling approaches suer from disturbances and noises and provide limited information of the system dynamics. In this thesis, a statistic (Bayesian Estimation) based distribution estimation approach is proposed for composite load models, including static (ZIP) and dynamic (Induction Motor) parts, by implementing Gibbs sampling. The proposed method provides a distribution estimation of coecients for load models and is robust to measurement errors. The overvoltage issue is another urgent issues need to be addressed, especially in a high PV penetration level system. Various approaches including the real power control through photovoltaic (PV) inverters have been proposed to mitigate such impact, however, most of the existing methods did not include communication delays in the control loop. Communication delays, short or long, are inevitable in the PV voltage regulation loop and can not only deteriorate the system performance with undesired voltage quality but also cause system instability. In this thesis, a method is presented to convert the overvoltage control problem via PV inverters for multiple PVs into a problem of single-input-single-output (SISO) systems. The method can handle multiple PVs and dierent communication delays. The impact of communication delays is also systematically analyzed and the maximum tolerable delay is rigorously obtained. Dierent from linear matrix inequality (LMI) techniques that have been extensively studied in handling systems with communication delays, the proposed method gives the necessary and sucient condition for obtaining a controller and the design procedure is explicitly and constructively given in the paper. The effectiveness of the proposed method is veried by simulation studies on a distribution feeder and the widely-used 33-bus distribution test system. The similar design strategy can be utilized to mitigate delay impacts in Load frequency control (LFC) as well. LFC has been considered as one of the most important frequency regulation mechanisms in modern power system. One of the inevitable problems involved in LFC over a wide area is communication delay. In this thesis, an alternative design method is proposed to devise delay compensators for LFC in one or multiple control areas. For one-area LFC, a sucient and necessary condition is given for designing a delay compensator. For multiarea LFC with area control errors (ACEs), it is demonstrated that each control area can have its delay controller designed as that in a one-area system if the index of coupling among the areas is below the threshold value determined by the small gain theorem. Effectiveness of the proposed method is veried by simulation studies on LFCs with communication delays in one and multiple interconnected areas with and without time-varying delays, respectively

Analysis And Mitigation Of The Impacts Of Delays In Control Of Power Systems With Renewable Energy Sources

ABSTRACT Analysis and Mitigation of the Impacts of Delays in Control of Power Systems with Renewable Energy Sources by Chang Fu Apr. 2019 Advisor : Dr. Caisheng Wang Major : Electrical and Computer Engineering Degree : Doctor of Philosophy With the integration of renewable resources, electric vehicles and other uncertain resources into power grid, varieties of control topology and algorithms have been proposed to increase the stability and reliability of the operation system. Load modeling is an critical part in such analysis since it significantly impacts the accuracy of the simulation in power system, as well as stability and reliability analysis. Traditional power system composite load model parameter identification problems can be essentially ascribed to optimization problems, and the identied parameters are point estimations subject to dierent constraints. These conventional point estimation based composite load modeling approaches suer from disturbances and noises and provide limited information of the system dynamics. In this thesis, a statistic (Bayesian Estimation) based distribution estimation approach is proposed for composite load models, including static (ZIP) and dynamic (Induction Motor) parts, by implementing Gibbs sampling. The proposed method provides a distribution estimation of coecients for load models and is robust to measurement errors. The overvoltage issue is another urgent issues need to be addressed, especially in a high PV penetration level system. Various approaches including the real power control through photovoltaic (PV) inverters have been proposed to mitigate such impact, however, most of the existing methods did not include communication delays in the control loop. Communication delays, short or long, are inevitable in the PV voltage regulation loop and can not only deteriorate the system performance with undesired voltage quality but also cause system instability. In this thesis, a method is presented to convert the overvoltage control problem via PV inverters for multiple PVs into a problem of single-input-single-output (SISO) systems. The method can handle multiple PVs and dierent communication delays. The impact of communication delays is also systematically analyzed and the maximum tolerable delay is rigorously obtained. Dierent from linear matrix inequality (LMI) techniques that have been extensively studied in handling systems with communication delays, the proposed method gives the necessary and sucient condition for obtaining a controller and the design procedure is explicitly and constructively given in the paper. The effectiveness of the proposed method is veried by simulation studies on a distribution feeder and the widely-used 33-bus distribution test system. The similar design strategy can be utilized to mitigate delay impacts in Load frequency control (LFC) as well. LFC has been considered as one of the most important frequency regulation mechanisms in modern power system. One of the inevitable problems involved in LFC over a wide area is communication delay. In this thesis, an alternative design method is proposed to devise delay compensators for LFC in one or multiple control areas. For one-area LFC, a sucient and necessary condition is given for designing a delay compensator. For multiarea LFC with area control errors (ACEs), it is demonstrated that each control area can have its delay controller designed as that in a one-area system if the index of coupling among the areas is below the threshold value determined by the small gain theorem. Effectiveness of the proposed method is veried by simulation studies on LFCs with communication delays in one and multiple interconnected areas with and without time-varying delays, respectively

Secure Control of Cyber-Physical Systems

Cyber-Physical Systems (CPS) are smart co-engineered interacting networks of physical and computational components. They refer to a large class of technologies and infrastructure in almost all life aspects including, for example, smart grids, autonomous vehicles, Internet of Things (IoT), advanced medical devices, and water supply systems. The development of CPS aims to improve the capabilities of traditional engineering systems by introducing advanced computational capacity and communications among system entities. On the other hand, the adoption of such technologies introduces a threat and exposes the system to cyber-attacks. Given the unique properties of CPSs, i.e. physically interacting with its environment, malicious parties might be interested in exploiting the physical properties of the system in the form of a cyber-physical attack. In a large class of CPSs, the physical systems are controlled using a feedback control loop. In this thesis, we investigate, from many angles, how CPSs' control systems can be prone to cyber-physical attacks and how to defend them against such attacks using arguments drawn from control theory. In our first contribution, by considering Smart Grid applications, we address the problem of designing a Denial of Service (DoS)-resilient controller for recovering the system's transient stability robustly. We propose a Model Predictive Control (MPC) controller based on the set-theoretic (ST) arguments, which is capable of dealing with both model uncertainties, actuator limitations, and DoS. Unlike traditional MPC solutions, the proposed controller has the capability of moving most of the required computations into an offline phase. The online phase requires the solution of a quadratic programming problem, which can be efficiently solved in real-time. Then, stemming from the same ST based MPC controller idea, we propose a novel physical watermarking technique for the active detection of replay attacks in CPSs. The proposed strategy exploits the ST-MPC paradigm to design control inputs that, whenever needed, can be safely and continuously applied to the system for an apriori known number of steps. Such a control scheme enables the design of a physical watermarked control signal. We prove that, in the attack-free case, the generators' transient stability is achieved for all admissible watermarking signals and that the closed-loop system enjoys uniformly ultimately bounded stability. In our second contribution, we address the attacker's ability to collect useful information about the control system in the reconnaissance phase of a cyber-physical attack. By using existing system identification tools, an attacker who has access to the control loop can identify the dynamics of the underlying control system. We develop a decoy-based moving target defense mechanism by leveraging an auxiliary set of virtual state-based decoy systems. Simulation results show that the provided solution degrades the attacker's ability to identify the underlying state-space model of the considered system from the intercepted control inputs and sensor measurements. It also does not impose any penalty on the control performance of the underlying system. Finally, in our third contribution, we introduce a covert channel technique, enabling a compromised networked controller to leak information to an eavesdropper who has access to the measurement channel. We show that this can be achieved without establishing any additional explicit communication channels by properly altering the control logic and exploiting robust reachability arguments. A dual-mode receding horizon MPC strategy is used as an illustrative example to show how such an undetectable covert channel can be established

Security of Cyber-Physical Systems

Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems

Effects of Time Delays in the Electric Power Grid

Communication delays in an electric power grid affect the performance of control systems and can cause power losses. This paper analyzes the causes and effects of communication delays. The analysis employs a simulated power network comprising several generators for which braking resistors with intelligent (fuzzy logic) controllers are used for transient stability control. A balanced 3LG (three-phase-to-ground) fault at different points on the transmission lines is considered. Simulation results show that, although a fuzzy-logic-controlled braking resistor can improve transient stability, the communication delay associated with the online calculation of the total kinetic energy deviation, which is the input parameter for fuzzy control, has an influence on the transient stability performance. The paper also examines the delay that a system can tolerate and the cyber attacks that can cause additional delays. © 2012 IFIP International Federation for Information Processing