To mitigate the technical challenges faced by the next-generation smart power grid, in this thesis, novel frameworks are developed for optimizing energy management and trading between power companies and grid consumers, who own renewable energy generators and storage units. The proposed frameworks explicitly account for the effect on demand-side energy management of various consumer-centric grid factors such as the stochastic renewable energy forecast, as well as the varying future valuation of stored energy. In addition, a novel approach is proposed to enhance the resilience of consumer-centric energy trading scenarios by analyzing how a power company can encourage its consumers to store energy, in order to supply the grid’s critical loads, in case of an emergency. The developed energy management mechanisms advance novel analytical tools from game theory, to capture the coupled actions and objectives of the grid actors and from the framework of prospect theory (PT), to capture the irrational behavior of consumers when faced with decision uncertainties. The studied PT and game-based solutions, obtained through analytical and algorithmic characterization, provide grid designers with key insights on the main drivers of each actor’s energy management decision. The ensuing results primarily characterize the difference in trading decisions between rational and irrational consumers, and its impact on energy management. The outcomes of this thesis will therefore allow power companies to design consumer-centric energy management programs that support the sustainable and resilient development of the smart grid by continuously matching supply and demand, and providing emergency energy reserves for critical infrastructure. / Master of Science / The next-generation smart power grid is seen as a key enabler for effectively generating, delivering, and consuming electricity in a sustainable manner. Given the increasing demand for energy and the limited nature of various energy resources, the exchange of energy between producers and consumers must be optimally managed to pave the way towards the deployment of smart grid features on a larger scale. In particular, energy management schemes must deal with a complex and dynamic smart grid composed of utility companies, traditional power sources and loads, intermittent renewable energy generators, as well as new consumer-owned devices such as energy storage units and solar panels. In this thesis, we seek to model the different entities in the smart grid and the exchange of energy between them, in order to better understand the operation and effectiveness of various energy management schemes. In addition, this thesis accounts for the non-rational behavior of consumers in the energy trading process, when faced with various sources of uncertainty in the smart grid, including the intermittent renewable energy generation and the dynamic energy price. The results of this thesis will provide utility companies with key insights, crucial to the design of consumer-centric energy management programs, aimed towards matching electricity supply and demand, and insuring power supply to critical infrastructure.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/78266 |
| Date | 26 June 2017 |
| Creators | El Rahi, Georges |
| Contributors | Electrical and Computer Engineering, Saad, Walid, Kekatos, Vasileios, Dhillon, Harpreet Singh |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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