University of Macau / Faculty of Science and Technology / Department of Electrical and Computer Engineering

Infrastructure systems are essential to the functioning of contemporary societies and economies. A major disruption to the built environment can lead to severe public safety issues and economic losses. Within the past few decades, modern control and information technologies have been rapidly developed in an attempt to improve the reliability of individual utility systems by exchanging technologies across them. One of the major ramifications is the emergence of interdependencies among these critical infrastructure systems, especially when facing major disruptions. Failure of an individual system becomes more likely to affect the functionality of other interconnected infrastructure systems. In order to mitigate such consequences, the mechanics of interdependencies and failure propagation among the systems must be understood. This research focuses on the development of a framework for probabilistically quantifying interdependent responses of two essential infrastructure systems - telecommunication and electric power systems - subjected to seismic hazards, which are one of the most powerful and geographically extensive threats. The study explores the effects of seismic hazards beyond the obvious seismic-induced physical damage to utility system facilities. In particular, the seismic evaluation of telecommunication systems considers the degradation of system performance due to physical damage and the abnormally high usage demands in telecommunication systems expected after catastrophic earthquakes. Specifically, a newly developed seismic-induced congestion model is proposed, and the probabilistic formulations of the critical interdependencies across telecommunication and power systems are presented in a probabilistic framework. The study illustrates the procedure for fragility analysis of interdependent systems and presents a practical application through a test bed implementation in Shelby County, TN. From this study, telecommunication systems are found to be very vulnerable to seismic-induced congestion. The electric power interdependencies amplify the degradation in telecommunication systems up to 50% in their vulnerability while electric power operations are heavily dependent upon telecommunication infrastructures and the fragility median of electric power system observability can decrease by 30%. The study also indicates up to 100% overestimation of the independent fragility analysis and the results reveal the relationship between system topology and the sensitivity of system performance to the intensity of interdependencies. The proposed methodology is expected to be a valuable tool for decision making in evaluating seismic mitigation strategies and also to provide the foundation for future studies on interdependent responses of other critical infrastructures.

Thesis (Ph. D.)--Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

Thesis (M. Phil.)--University of Hong Kong, 1989.

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

To combat global climate change, the reduction of carbon emissions in different industries, particularly the power industry, has been gradually moving towards a low-carbon profile to alleviate any irreversible damage to the planet and our future generations. Traditional fossil-fuel-based generation is slowly replaced by more renewable energy generation while it can be harnessed. However, renewables such as solar and wind are stochastic in nature and difficult to predict accurately. With the increasing content of renewables, there is also an increasing challenge to the planning and operation of the grid. With the rapid deployment of smart meters and advanced metering infrastructure (AMI), an emerging approach is to schedule controllable end-use devices to improve energy efficiency. Real-time pricing signals combined with this approach can potentially deliver more economic and environmental advantages compared with the existing common flat tariffs. Motivated by this, the thesis presents an automatic and optimal load scheduling framework to help balance intermittent renewables via the demand side. A bi-level consumer-utility optimization model is proposed to take marginal price signals and wind power into account. The impact of wind uncertainty is formulated in three different ways, namely deterministic value, scenario analysis, and cumulative distributions function, to provide a comprehensive modeling of unpredictable wind energy. To solve the problem in off-the-shelf optimization software, the proposed non-linear bi-level model is converted into an equivalent single-level mixed integer linear programming problem using the Karush-Kuhn-Tucker optimality conditions and linearization techniques. Numerical examples show that the proposed model is able to achieve the dual goals of minimizing the consumer payment as well as improving system conditions. The ultimate goal of this work is to provide a tool for utilities to consider the demand response model into their market-clearing procedure. As high penetration of distributed renewable energy resources are most likely applied to remote or stand-alone systems, planning such systems with uncertainties in both generation and demand sides is needed. As such, a three-level probabilistic sizing methodology is developed to obtain a practical sizing result for a stand-alone photovoltaic (PV) system. The first-level consists of three modules: 1) load demand, 2) renewable resources, and 3) system components, which comprise the fundamental elements of sizing the system. The second-level consists of various models, such as a Markov chain solar radiation model and a stochastic load simulator. The third-level combines reliability indices with an annualized cost of system to form a new objective function, which can simultaneously consider both system cost and reliability based on a chronological Monte Carlo simulation and particle swamp optimization approach. The simulation results are then tested and verified in a smart grid laboratory at the University of Hong Kong to demonstrate the feasibility of the proposed model. In summary, this thesis has developed a comprehensive framework of demand response on variable end-use consumptions with stochastic generation from renewables while optimizing both reliability and cost. Smart grid technologies, such as renewables, microgrid, storage, load signature, and demand response, have been extensively studied and interactively modeled to provide more intelligent planning and management for the smart grid. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

D. Tech. Electrical Engineering. / Discusses the operations and planning of power systems is a complex task, mostly with many intricate manoeuvres to ensure reliable network operations such that the active power losses are reduced and the network voltage proles are improved without compromising the network security. Then the question is, what is the role of the inherent structural characteristics in solving power system problems? Although, the inherent structural characteristics of a power system network are embedded within the load flow formulation to some extent, their full capabilities in solving the problems of the network have not been holistically investigated. The fundamental circuit theory law (Ohm's law), which is a linear equation, clearly demonstrates the importance of the structural topology of the network. However, this importance is confounded by the reformulation of the fundamental law to nonlinear load flow equations. This research investigated the role of the inherent structural characteristics in solving power system problems from a circuit theory perspective.

published_or_final_version / Electrical Engineering / Master / Master of Philosophy

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