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DESIGN, IMPLEMENTATION, AND EVALUATION OF NAPALI: A NOVEL DISTRIBUTED SENSOR NETWORK FOR IMPROVED POWER QUALITY MONITORING.
|Title:||DESIGN, IMPLEMENTATION, AND EVALUATION OF NAPALI: A NOVEL DISTRIBUTED SENSOR NETWORK FOR IMPROVED POWER QUALITY MONITORING.|
|Contributors:||Johnson, Philip (advisor)|
Computer Science (department)
|Publisher:||University of Hawai'i at Manoa|
|Abstract:||Today’s big data world heavily relies upon providing precise, timely, and actionable intelligence,|
while being burdened by the ever increasing need for data cleaning and preprocessing. While in the
case of ingesting large quantity of unstructured data this problem is unavoidable, when it comes to
sensor networks built for a specific purpose, such as anomaly detection, some of that computation
can be moved to the edge of the network. This thesis concerns the special case of sensor networks
tailored for monitoring the power grid for anomalous behavior. These networks monitor power
delivery infrastructure with the intent of finding deviations from the nominal steady state, across
multiple geographical locations. Aforementioned deviations, known as power quality anomalies,
may originate, and be localized to the location of the sensor, or may affect a sizable portion of the
power grid. The difficulty of evaluating the extent of a power quality anomaly stems directly from
their short temporal and variable geographical impact. I present a novel distributed power quality
monitoring system called Napali which relies on extracted metrics from individual meters and their
temporal locality in order to intelligently detect anomalies and extract raw data within temporal
window and geographical areas of interest.
The claims of this thesis are that Napali outperforms existing power quality monitoring gridwide
event detection methods in resource utilization and sensitivity. Furthermore, Napali residential
monitoring is capable of power grid monitoring without deployment on the high voltage transmission
lines. Final claim of this thesis is that Napali capability of extracting portions of the events which
did not pass the critical thresholds used in other detection methods allows for better localization
of power quality disturbances. Napali claim validation was performed through deployment at the
University of Hawaii. Fifteen OPQ Box devices, designed specifically to operate with Napali were
located in various locations on campus. Data collected from these monitors was compared with
smart meters already deployed across the University. Additionally, Napali was compared with
standard methods of power quality event detection running along side the Napali systems.
Napali methodology outperformed the standard methods of power quality monitoring in resource
consumption, event quality and sensitivity. Additionally, I was able to validate that residential
utility monitoring is capable of event detection and localization without monitoring higher levels
of the power grid hierarchy. Finally, as a demonstration of Napali capabilities, I showed how data
collected by my framework can be used to partition the power delivery infrastructure without prior
knowledge of the power grid topology.
|Rights:||All UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.|
|Appears in Collections:||
Ph.D. - Computer Science|
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