@article{25771,
  keywords = {Demand response, Demand response and distributed energy resources center, Demand Response Research Center (DRRC), Peak demand, Thermal mass, Demand shifting (pre-cooling), DRQAT, Auto-dr, Demand shed, Pre-cooling},
  author = {Rongxin Yin and Peng Xu and Mary Ann Piette and Sila Kiliccote},
  title = {Study on Auto-DR and Pre-cooling of Commercial Buildings with Thermal Mass in California},
  abstract = {<p>This paper studies how to optimize pre-cooling strategies for buildings in a hot climate zone of California with the assistance of a building energy simulation tool - Demand Response Quick Assessment Tool (DRQAT). This paper outlines the procedure to develop and calibrate simulation models by using DRQAT, and then applies this procedure into 11 field test buildings. Through comparing the measured demand savings during the peak period with those of simulation model, the results indicate that the predicted demand shed match well with the actual data on Auto-DR days. The study shows that after refining and calibrating initial models with actual measured data, the accuracy of the models can be greatly improved and the models can be used to predict load reductions for automated demand response events. In order to confirm the actual effect of demand response strategies, the simulation results were compared with field test data as well. The results indicated that the optimal demand response strategies worked well for most of buildings in hot climate zone.</p>},
  year = {2010},
  journal = {Energy and Buildings},
  volume = {42},
  edition = {January 2010},
  number = {7},
  pages = {967-975},
  month = {07/2010},
  note = {<p>received 7/11/09, revised 1/8/10, accepted 1/9/10</p>},
  language = {eng},
}