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Author ORCID Identifier
https://orcid.org/0000-0002-6366-5320
AccessType
Open Access Dissertation
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Electrical and Computer Engineering
Year Degree Awarded
2023
Month Degree Awarded
September
First Advisor
Jay Taneja
Second Advisor
David Irwin
Third Advisor
Prashant Shenoy
Fourth Advisor
Gabriel Cadamuro
Subject Categories
Data Science | Power and Energy
Abstract
Over the past few years, the world has witnessed a dramatic increase in the efforts towards ending energy poverty. Out of the 17 Sustainable Development Goals (SDG) proposed by the United Nations (UN), the SDG 7 was specifically established to ensure affordable, reliable, sustainable and modern energy for all by 2030. As a result, governments and international organizations the world over have been investing millions of dollars into building new electric grid infrastructure and improving the quality and reliability of the existing ones. However, the methods and tools to track electrification efforts and monitor grid health -- reliability and power quality -- are inconsistent, inaccurate, expensive and often out of reach due to various budget, resource and political constraints. Without sufficient information about the grid, energy system planners struggle to identify the next set of areas to electrify, utilities struggle to provision reliable and good quality supply of electricity, and customers struggle to thrive. To address this shortcoming, in this thesis, we develop and demonstrate side channel measurement techniques for high resolution monitoring of electricity grids at scale. Specifically, our novel contributions include: (i) tracking electrification progress using high resolution daytime satellite images, (ii) monitoring power grid supply inconsistencies using daily nighttime lights satellite data, and (iii) measuring power quality at the end-points of distribution grid using digital cameras. We discuss the challenges associated with building deployable solutions for low-cost worldwide measurements of reliability and power quality, and particularly demonstrate our contributions towards estimating electricity reliability at a global scale.
DOI
https://doi.org/10.7275/36029866
Recommended Citation
Shah, Zeal P., "Side-Channel Measurement Techniques for Monitoring Electricity Grids" (2023). Doctoral Dissertations. 2986.
https://doi.org/10.7275/36029866
https://scholarworks.umass.edu/dissertations_2/2986
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.