Long Zhao

ORCID Identifier(s)

0000-0003-1710-4431

Graduation Semester and Year

2020

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Electrical Engineering

Department

Electrical Engineering

First Advisor

Wei-Jen Lee

Abstract

The Internet-of-Things (IoT) concept allows objects to share data through wired or wireless connections for communication purposes. Currently, IoT has been involved with the development of smart grids in many applications. In this article-based dissertation, IoT applications in power systems are presented in 7 published research papers. In the first three papers, the developments of the IoT-based monitoring system are presented. Power substation monitoring for the petrochemical facility is discussed in the first paper. Internal design and detection mechanisms are emphasized in this research. The second paper presents the communication and task allocations for a generic power substation monitoring system. The third paper shows a holistic monitoring system for wind turbine considering both Subsynchronous Control Interaction detection and condition monitoring. The fourth and fifth papers presented a study for demand-side management (DSM) at the residential level and commercial level respectively. Comparing with traditional power meters, smart meters can provide much more detailed information that can be applied in IoT applications such as DSM. In the fourth paper, the research is to examine the key reasons for the underlying ineffectiveness/effectiveness of one type of DSM programs at the residential level using real residential smart meter data. In the fifth paper, the potential of DSM for commercial consumers is analyzed considering energy storage based on real smart meter data of commercial consumers. In the sixth paper, a new approach for arc flash fault detection by using the spectrum of the light is developed in this research. By examining the spectrum of the light, arc flash can be accurately and quickly detected. This research is being extended for arcing fault type identification with IoT technology to improve the current arc flash protection operation and provide more detailed information for system operators, and it is presented in the last paper.

Keywords

Arc flash, Demand response, Demand side management, IoT, Monitoring, Power systems, Smart grid

Disciplines

Electrical and Computer Engineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

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