Demand response implementation for improved system efficiency in remote communities

Michael Wrinch, Greg Dennis, Tarek H.M. El-Fouly, Steven Wong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

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.

Original languageBritish English
Title of host publication2012 IEEE Electrical Power and Energy Conference, EPEC 2012
Pages105-110
Number of pages6
DOIs
StatePublished - 2012
Event2012 IEEE Electrical Power and Energy Conference, EPEC 2012 - London, ON, Canada
Duration: 10 Oct 201212 Oct 2012

Publication series

Name2012 IEEE Electrical Power and Energy Conference, EPEC 2012

Conference

Conference2012 IEEE Electrical Power and Energy Conference, EPEC 2012
Country/TerritoryCanada
CityLondon, ON
Period10/10/1212/10/12

Keywords

  • Demand Response
  • Energy Conservation
  • Energy Control
  • Energy Management
  • Implementation Challenges
  • Load Prediction
  • Smart Grids

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