DocumentCode :
3509008
Title :
Demand response implementation for improved system efficiency in remote communities
Author :
Wrinch, M. ; Dennis, G. ; EL-Fouly, Tarek H. M. ; Wong, Simon
Author_Institution :
Smart Syst. & Analytics Group, Pulse Energy Inc., Vancouver, BC, Canada
fYear :
2012
fDate :
10-12 Oct. 2012
Firstpage :
105
Lastpage :
110
Abstract :
This paper evaluates the performance of a demand response (DR) system, installed in the remote community of Hartley Bay, British Columbia, which is used to reduce fuel consumption during periods of peak loads and poor fuel efficiency. The DR system, installed to shed load during these periods, is capable of shedding up to 15 per cent of maximum demand by adjusting wireless variable thermostats and load controllers on hot water heaters and ventilation systems in commercial buildings. The system was found to be successful in reducing demand by up to 35 kW during the DR event period, but caused a new, time-shifted “rebound” peak of 30 to 50 per cent following each event. A DR “staggering” method is introduced as a tool for reducing and delaying rebound without affecting occupant comfort and safety. In this work, load prediction models based on linear regression and averaging of historical data were also developed for measuring DR shed and rebound, with models based on averaging found to produce more accurate baselines.
Keywords :
load regulation; load shedding; regression analysis; space heating; thermostats; ventilation; British Columbia; DR event period; DR shed-rebound; DR staggering method; DR system; Hartley Bay; commercial buildings; demand response implementation; fuel consumption reduction; fuel efficiency; historical data averaging; hot water heaters; improved system efficiency; linear regression; load controllers; load prediction model; load shedding; remote communities; time-shifted rebound peak; ventilation systems; wireless variable thermostats; Buildings; Communities; Data models; Fuels; Generators; Load modeling; Predictive models; Demand Response; Energy Conservation; Energy Control; Energy Management; Implementation Challenges; Load Prediction; Smart Grids;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Power and Energy Conference (EPEC), 2012 IEEE
Conference_Location :
London, ON
Print_ISBN :
978-1-4673-2081-8
Electronic_ISBN :
978-1-4673-2079-5
Type :
conf
DOI :
10.1109/EPEC.2012.6474932
Filename :
6474932
Link To Document :
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