@techreport{56061,
  keywords = {Demand response, Thermal mass, Demand shifting (pre-cooling), Pre-cooling},
  author = {Peng Xu and Leah Zagreus},
  title = {Demand Shifting With Thermal Mass in Light and Heavy Mass Commercial Buildings},
  abstract = {<p>The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies. This project studied the potential of pre-cooling and demand limiting in a heavy mass and a light mass building in the Bay Area of California. The conclusion of the work to date is that pre-cooling has the potential to improve the demand responsiveness of commercial buildings while maintaining acceptable comfort conditions. Results indicate that pre-cooling increases the depth (kW) and duration (kWh) of the shed capacity of a given building, all other factors being equal. Pre-cooling and demand shed strategies worked well in both the light and heavy mass buildings. A properly-controlled <em>exponential temperature set up</em> strategy in the shed period discharged thermal mass smoothly in both buildings. The optimal strategy for avoiding rebound was an <em>exponential temperature reset</em> strategy. Pre-cooling was very effective even in cool weather conditions in the heavy mass building. Night pre-cooling had noticeable effects on the second day cooling load in the heavy mass building. Night pre-cooling reduced both HVAC peak demand and energy consumption in cool weather in the heavy mass building. Due to the time necessary for pre-cooling, it is only applicable to day-ahead demand response programs. The effectiveness of night pre-cooling under hot weather conditions has not been tested. Further work is required to quantify and demonstrate the effectiveness of pre-cooling in different climates. Research is also needed on occupant response with advance notification of the pre-cooling DR event. Further work is necessary to develop screening tools that can be used to select suitable buildings and customers, identify the most appropriate pre-cooling strategies, and estimate the benefits to the customer and the utility.</p>},
  year = {2006},
}