@misc{27302,
  author = {Rongxin Yin and Douglas R Black},
  title = {Improvement Of Demand Response Quick Assessment Tool (DRQAT) and Tool Validation Case Studies},
  abstract = {<p>In 2006, the Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory (LBNL) initiated the development of a quick assessment tool for demand response in buildings and, in 2007 the DRRC released the first version of the Demand Response Quick Assessment Tool (DRQAT) for public use. Over the past few years, the DRRC has been improving the DRQAT tool based on users’ feedback and upgrading the engine with the EnergyPlus energy simulation tool. Currently, DRQAT enables users to evaluate a single DR strategy configuration at a time. Users could greatly benefit from being able to run multiple strategy configurations at a time and directly compare their performance in a single output report. The latest update of DRQAT, described in this report, enables users to do just that to compare different pre-cooling and reset strategies. Also, to help customers better understand the demand response performance of their facilities; this report presents several case studies to compare demand response predictions with measured values. A previous study indicated that the predictive value of the DRQAT simulation model could be significantly improved after calibrating the model with measured data. Most users are not familiar with model calibration, a process that can be time consuming. This report shows a comparison of DRQAT results generated as a typical user would—without calibration. The results show that the DRQAT tool can generate credible predictions of peak demand savings and load shapes throughout demand response event hours.</p>},
  year = {2015},
  month = {08/2015},
}