Optimal and Resilient Control with Applications in Smart Distribution Grids
Abstract: The electric power industry and society are facing the challenges and opportunitiesof transforming the present power grid into a smart grid. To meetthese challenges, new types of control systems are connected over IT infrastructures.While this is done to meet highly set economical and environmentalgoals, it also introduces new sources of uncertainty in the control loops. Inthis thesis, we consider control design taking some of these uncertainties intoaccount.In Part I of the thesis, some economical and environmental concerns insmart grids are taken into account, and a scheduling framework for staticloads (e.g., smart appliances in residential areas) and dynamic loads (e.g., energystorage systems) in the distribution level is investigated. This frameworkaims to reduce both the electricity bill and the CO2 emissions in residentialareas. A robust formulation is proposed taking the user behavior uncertaintyinto account, so that the optimal scheduling cost is less sensitive tounpredictable changes in user preferences. In addition, a novel distributedalgorithm for the studied scheduling framework is proposed, which aims atminimizing the aggregated electricity cost of a network of apartments sharingan energy storage system. The proposed approach guarantees cooperationamong consumers, and fairness in the use of the shared resources. We pointout that the proposed scheduling framework is applicable to various uncertaintysources, storage technologies, and programmable electrical loads.In Part II of the thesis, we study smart grid uncertainty resulting frompossible security threats. Smart grids are one of the most complex cyberphysicalsystems considered, and are vulnerable to various cyber and physicalattacks. These threats can affect the smart grid in different aspects such asefficiency, safety, reliability and robustness. We identify potential vulnerabilitiesin the interface between the physical and the IT infrastructures of thepower system. These vulnerabilities may lead to an abnormal operation of thedistribution network. In particular, relevant attack scenarios are introduced,together with their threat models, based on which impact analysis is beingperformed. The attack scenarios consider cyber adversaries that may corrupta few measurements and reference signals, which may degrade the system’sreliability and even destabilize the voltage magnitudes. In addition, a practicalattack-resilient framework for networked control systems is proposed.This framework includes security information analytics to detect attacks anda resiliency policy to improve the performance of the system running underthe attack. Stability and optimal performance of the networked control systemunder attack and by applying the proposed framework, is proved here.The framework has been applied to an energy management system and itsefficiency is demonstrated on a critical attack scenario.
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