A fast method to predict the demand response peak load reductions of commercial buildings. (17th August 2016)

• Record Type: Journal Article
• Authors: Li, Weilin; Xu, Peng
• Is Part Of: Science and technology for the built environment. Volume 22:Number 6(2016)
• Page Start: 633
• Page End: 642
• Publication Date: 2016-08-17
• Subjects: Heating -- Periodicals; Ventilation -- Periodicals; Air conditioning -- Periodicals; Refrigeration and refrigerating machinery -- Periodicals; Indoor air quality -- Periodicals; Indoor air quality; Air conditioning; Heating; Refrigeration and refrigerating machinery; Ventilation; Periodicals; 697
• DOI: 10.1080/23744731.2016.1145533
• Languages: English
• ISSNs: 2374-474X

Abstract

Abstract : Demand response has become an increasingly important part of building control. However, before building owners and operators agree to participate in demand response programs with utility companies, knowledge of the maximum peak load that can be shifted in their buildings, as well as the economic benefits, is required. Engineers need to be able to predict the peak load reductions before control strategies are implemented. A good way to overcome difficulties in the prediction is via building performance simulations, but modeling a large commercial building in detail requires significant efforts and becomes very complicated. In demand response simulations, the accuracy of the peak load reduction is more important than the full-year energy performance. Therefore, this research proposes a facile simulation method for the accurate prediction of peak load reductions. This novel method is built on the basis of EnergyPlus with many simplifications and defaults. The principles of these simplifications and defaults are explained through thermal balance analysis, and the accuracy of the new demand response prediction method is verified through a case study completed in California.