Sponsor
Portland State University. Department of Electrical and Computer Engineering
First Advisor
Robert Bass
Date of Publication
Summer 9-5-2014
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Electrical and Computer Engineering
Department
Electrical and Computer Engineering
Language
English
Subjects
Electric power distribution -- Management, Electric transformers, Electric vehicles -- Energy consumption, Dwellings -- Energy consumption
DOI
10.15760/etd.1966
Physical Description
1 online resource (ix, 58 pages)
Abstract
Installation and utilization of residential distribution transformers has not changed substantially over a long period of time. Utilities typically size their transformers based on a formula that takes into account broadly what types and how many dwellings will be connected.
Most new residential dwellings feature 200 Amp service per household with an anticipated energy demand of under 20,000 kWh per year. Average electrical energy consumption varies from state to state but averages to 11,280 kWh per year. Energy demand is expected to fall into a typical residential load curve that shows increased demand early in the morning, then decreasing during the day and another peak early to late evening. Distribution transformers are sized at the limit of the combined evening peak with the assumption that the transformer has enough thermal mass to absorb short overloads that may occur when concurrent loading situations among multiple dwellings arise. The assumption that concurrent loading is of short duration and the transformer can cool off during the night time has been validated over the years and has become standard practice. This has worked well when dwelling loads follow an averaging scheme and low level of coincidence.
With the arrival of electric vehicles (EV's) this assumption has to be reevaluated. The acquisition of an electric vehicle in a household can drive up energy demand by over 4000 kWh per year. Potentially problematic is the increased capacity of battery packs and the resulting proliferation of Level 2 chargers. The additional load of a single Level 2 charger concurring with the combined evening peak load will push even conservatively sized distribution transformers over their nameplate rating for a substantial amount of time. Additionally, unlike common household appliances of similar power requirements such as ovens or water heaters, a Level 2 battery charger will run at peak power consumption for several hours, and the current drawn by the EVs has very high levels of harmonic distortion. The excessive loading and harmonic profile can potentially result in damaging heat build-up resulting in asset degradation.
In this thesis I present a device and method that monitors pole mounted distribution transformers for overheating, collect and wirelessly upload data and initiate commands to chargers to change output levels from Level 2 to Level 1 or shut down EV charging altogether until the transformer returns into safe operational range.
Rights
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Persistent Identifier
http://archives.pdx.edu/ds/psu/12558
Recommended Citation
Zumr, Zdenek, "Last Mile Asset Monitoring: Low Cost Rapid Deployment Asset Monitoring" (2014). Dissertations and Theses. Paper 1967.
https://doi.org/10.15760/etd.1966