Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Li, Pan
Committee Member
Topsakal, Erdem
Committee Member
Fowler, James E.
Committee Member
Du, Qian
Committee Member
Fu, Yong
Date of Degree
8-14-2015
Document Type
Dissertation - Open Access
Major
Electrical and Computer Engineering
Degree Name
Doctor of Philosophy (Ph.D)
College
James Worth Bagley College of Engineering
Department
Department of Electrical and Computer Engineering
Abstract
Despite the importance of power systems in today’s societies, they suffer from aging infrastructure and need to improve the efficiency, reliability, and security. Two issues that significantly limit the current grid’s efficient energy delivery and consumption are: loadollowing generation dispatch, and energy theft. A loadollowing generation dispatch is usually employed in power systems, which makes continuous small changes so as to account for differences between the actual energy demand and the predicted values. This approach has led to an average utilization of energy generation capacity below 55% [49]. Moreover, energy theft causes several billion dollar losses to U.S. utility companies [31] [16], while in developing countries it can amount to 50% of the total energy delivered [48]. Recently, the Smart Grid has been proposed as a new electric grid to modernize current power grids and enhance its efficiency, reliability, and sustainability. Particularly, in the Smart Grid, a digital communication network is deployed to enable two-way communications between users and system operators. It thus makes it possible to shape the users’ load demand curves by means of demand response strategies. Additionally, in the Smart Grid, traditional meters will be replaced with cyber-physical devices, called smart meters, capable of recording and transmitting users’ real-time power consumption. Due to their monitoring capabilities, smart meters offer a great opportunity to detect energy theft in smart grids, but also raise serious concerns about users’ privacy. In this dissertation, we design optimal load scheduling schemes to enhance system efficiency, and develop energy theft detection algorithms that can preserve users’ privacy.
URI
https://hdl.handle.net/11668/21093
Recommended Citation
Salinas Monroy, Sergio Alfonso, "Energy Management and Privacy in Smart Grids" (2015). Theses and Dissertations. 1877.
https://scholarsjunction.msstate.edu/td/1877