DocumentCode
725383
Title
Sensor Node to Improve Resiliency and Monitoring in Smart Grids: Taking the Lab to Field in Industry
Author
Russell, Luke ; Goubran, Rafik ; Kwamena, Felix
Author_Institution
Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
fYear
2015
fDate
10-12 June 2015
Firstpage
208
Lastpage
209
Abstract
Sensors and data analytics have a tremendous potential to improve the resilience of the electricity system. Improving the analytics in a smart grid, and providing information to operators so that problems can be resolved quickly, may serve to improve the resiliency of the electricity system. Effective use of sensors and analytics will enable more timely a response, and more efficient use of personnel, specialty equipment, and site location specifics because of better information for deployment teams to address damage. Detection of physical characteristics such as vibration, ice build up, hot spots, aging and deterioration of assets/equipment, metal fatigue and other considerations could prevent disruptions. In cold climates, ice storms can cause outages, and extreme weather events are constantly a threat to electricity towers. A system was developed to collect information from sensors, as well as relevant analytics to detect abnormalities to address damage, and for operator visualizations screens.
Keywords
condition monitoring; distributed sensors; electrical maintenance; power system measurement; power system reliability; sensor placement; smart power grids; aging detection; asset deterioration; equipment deterioration; hot spot detection; ice build-up detection; metal fatigue; sensor node; smart grid monitoring; smart grid resiliency; vibration detection; Data visualization; Ice; Microcontrollers; Monitoring; Poles and towers; Vibrations; Wires; Microcontrollers; accelerometer; magnetometer; smart grid;
fLanguage
English
Publisher
ieee
Conference_Titel
Distributed Computing in Sensor Systems (DCOSS), 2015 International Conference on
Conference_Location
Fortaleza
Type
conf
DOI
10.1109/DCOSS.2015.41
Filename
7165042
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