<p dir="ltr">The safe and reliable delivery of electricity is critical for the functioning of our modern society. However, high-impact, low-probability (HILP) catastrophic events (such as extreme weather caused by climate change, or cyber-physical attacks) pose an ever-growing threat to the power grid. At the same time, modern advancements in computational capabilities, communication infrastructure, and measurement technologies provide opportunities for new operation and control strategies that enhance the resilience of electric power systems to such HILP events. In this work, optimization-based operation and control approaches are proposed to improve resilience in two power systems applications. First, a real-time linearized-trajectory model-predictive controller (LTMPC) is developed for ensuring voltage, frequency, and transient (rotor angle) stability in systems engineered to operate as microgrids. Such microgrids are capable of seamlessly transitioning from grid-connected operation to an islanded mode and thus, enhance system resilience. The proposed LTMPC enables rapid deployment of such systems by reducing engineering costs and development time while maintaining stable operation. On the other hand, some power systems, such as distribution feeders, are not designed to operate as standalone microgrids. For these cases, a method is proposed for forming ad-hoc microgrids from intact sections of the damaged feeder in the aftermath of a HILP event. A feeder operating center-on-a-laptop (FOCAL) is introduced that coordinates the control of possibly hundreds of inverter-interfaced distributed energy resources (e.g., rooftop solar, battery storage) to improve system resilience. Theoretical analysis as well as numerical case studies and simulations of the proposed strategies are presented for both applications.</p>

The enhancement of the reliability, security, and resiliency of electric power systems depends on the availability of fast, accurate, and robust dynamic state estimators. These estimators should be robust to gross errors on the measurements and the model parameter values while providing good state estimates even in the presence of large dynamical system model uncertainties and non-Gaussian thick-tailed process and observation noises. It turns out that the current Kalman filter-based dynamic state estimators given in the literature suffer from several important shortcomings, precluding them from being adopted by power utilities for practical applications. To be specific, they cannot handle (i) dynamic model uncertainty and parameter errors; (ii) non-Gaussian process and observation noise of the system nonlinear dynamic models; (iii) three types of outliers; and (iv) all types of cyber attacks. The three types of outliers, including observation, innovation, and structural outliers are caused by either an unreliable dynamical model or real-time synchrophasor measurements with data quality issues, which are commonly seen in the power system. To address these challenges, we have pioneered a general theoretical framework that advances both robust statistics and robust control theory for robust dynamic state and parameter estimation of a cyber-physical system. Specifically, the generalized maximum-likelihood-type (GM)-estimator, the unscented Kalman filter (UKF), and the H-infinity filter are integrated into a unified framework to yield various centralized and decentralized robust dynamic state estimators. These new estimators include the GM-iterated extended Kalman filter (GM-IEKF), the GM-UKF, the H-infinity UKF and the robust H-infinity UKF. The GM-IEKF is able to handle observation and innovation outliers but its statistical efficiency is low in the presence of non-Gaussian system process and measurement noise. The GM-UKF addresses this issue and achieves a high statistical efficiency under a broad range of non-Gaussian process and observation noise while maintaining the robustness to observation and innovation outliers. A reformulation of the GM-UKF with multiple hypothesis testing further enables it to handle structural outliers. However, the GM-UKF may yield biased state estimates in presence of large system uncertainties. To this end, the H-infinity UKF that relies on robust control theory is proposed. It is shown that H-infinity is able to bound the system uncertainties but lacks of robustness to outliers and non-Gaussian noise. Finally, the robust H-infinity filter framework is proposed that leverages the H-infinity criterion to bound system uncertainties while relying on the robustness of GM-estimator to filter out non-Gaussian noise and suppress outliers. Furthermore, these new robust estimators are applied for system bus frequency monitoring and control and synchronous generator model parameter calibration. Case studies of several different IEEE standard systems show the efficiency and robustness of the proposed estimators. / Ph. D.

Vehicle Dynamics Control (VDC) systems (also known as Active Chassis systems) are mechatronic systems developed for improving vehicle comfort, handling and/or stability. Traditionally, most of these systems have been individually developed and manufactured by various suppliers and utilised by automotive manufacturers. These decentralised control systems usually improve one aspect of vehicle performance and in some cases even worsen some other features of the vehicle. Although the benefit of the stand-alone VDC systems has been proven, however, by increasing the number of the active systems in vehicles, the importance of controlling them in a coordinated and integrated manner to reduce the system complexity, eliminate the possible conflicts as well as expand the system operational envelope, has become predominant. The subject of Integrated Vehicle Dynamics Control (IVDC) for improving the overall vehicle performance in the existence of several VDC active systems has recently become the topic of many research and development activities in both academia and industries Several approaches have been proposed for integration of vehicle control systems, which range from the simple and obvious solution of networking the sensors, actuators and processors signals through different protocols like CAN or FlexRay, to some sort of complicated multi-layered, multi-variable control architectures. In fact, development of an integrated control system is a challenging multidisciplinary task and should be able to reduce the complexity, increase the flexibility and improve the overall performance of the vehicle. The aim of this thesis is to develop a low-cost control scheme for integration of Electric Power-Assisted Steering (EPAS) system with Enhanced Stability Program (ESP) system to improve driver comfort as well as vehicle safety. In this dissertation, a systematic approach toward a modular, flexible and reconfigurable control architecture for integrated vehicle dynamics control systems is proposed which can be implemented in real time environment with low computational cost. The proposed control architecture, so named “Integrated Vehicle Control System (IVCS)”, is customised for integration of EPAS and ESP control systems. IVCS architecture consists of three cascade control loops, including high-level vehicle control, low-level (steering torque and brake slip) control and smart actuator (EPAS and EHB) control systems. The controllers are designed based on Youla parameterisation (closed-loop shaping) method. A fast, adaptive and reconfigurable control allocation scheme is proposed to coordinate the control of EPAS and ESP systems. An integrated ESP & ESP HiL/RCP system including the real EPAS and Electro Hydraulic Brake (EHB) smart actuators integrated with a virtual vehicle model (using CarMaker/HiL®) with driver in the loop capability is designed and utilised as a rapid control development platform to verify and validate the developed control systems in real time environment. Integrated Vehicle Dynamic Control is one of the most promising and challenging research and development topics. A general architecture and control logic of the IVDC system based on a modular and reconfigurable control allocation scheme for redundant systems is presented in this research. The proposed fault tolerant configuration is applicable for not only integrated control of EPAS and ESP system but also for integration of other types of the vehicle active systems which could be the subject of future works.

The design of an attitude control system for a flexible spacecraft using magnetic actuation is considered. The nonlinear, linear, and modal equations of motion are developed for a general flexible body. Magnetic control is shown to be instantaneously underactuated, and is only controllable in the time-varying sense. A PD-like control scheme is proposed to address the attitude control problem for the linear system. Control gain limitations are shown to exist for the purely magnetic control. A hybrid control scheme is also proposed that relaxes these restrictions by adding a minimum control effort from an alternate three-axis actuation system. Floquet and passivity theory are used to obtain gain selection criteria that ensure a stable closed-loop system, which would aid in the design of a hybrid controller for a flexible spacecraft. The ability of the linearized system to predict the stability of the corresponding nonlinear system is also investigated.

The design of an attitude control system for a flexible spacecraft using magnetic actuation is considered. The nonlinear, linear, and modal equations of motion are developed for a general flexible body. Magnetic control is shown to be instantaneously underactuated, and is only controllable in the time-varying sense. A PD-like control scheme is proposed to address the attitude control problem for the linear system. Control gain limitations are shown to exist for the purely magnetic control. A hybrid control scheme is also proposed that relaxes these restrictions by adding a minimum control effort from an alternate three-axis actuation system. Floquet and passivity theory are used to obtain gain selection criteria that ensure a stable closed-loop system, which would aid in the design of a hybrid controller for a flexible spacecraft. The ability of the linearized system to predict the stability of the corresponding nonlinear system is also investigated.