A web-based Roof Savings Calculator (RSC) has been deployed for the United States Department of Energy as an industry – consensus tool to help building owners, manufacturers, distributors, contractors and researchers easily run complex roof and attic simulations. This tool employs modern web technologies, usability design, and national average defaults as an interface to annual simulations of hour–by -hour, whole -building performance using the world-class simulation tools DOE-2.1E and AtticSim in order to provide estimated annual energy and cost savings from reduced HVAC use.
In addition to cool reflective roofs, RSC simulates multiple roof and attic configurations including different roof slopes, above sheathing ventilation, radiant barriers, low-emittance roof surfaces, duct location, duct leakage rates, multiple substrate types, and insulation levels. A base case and energy-efficient alternative can be compared side-by-side to estimate monthly energy consumption. RSC was benchmarked against field data from demonstration homes in Ft. Irwin, California; while cooling savings were similar, heating penalty varied significantly across different simulation engines. RSC results show reduced cool roofing cost-effectiveness thus mitigating expected economic incentives for this countermeasure to the urban heat island effect.
This paper consolidates comparison of RSC’s projected energy savings to other simulation engines including DOE2.1E, AtticSim, Micropas, and EnergyPlus, and presents the preliminary analyses. RSC’s algorithms for capturing radiant heat transfer and duct interaction in the attic assembly are considered major contributing factors toward slightly increased cooling savings offset by larger heating penalties. Comparison to previous simulation-based studies, analysis on the force multiplier of RSC cooling savings and heating penalties, the role of radiative heat exchange in an attic assembly, and changes made for increased accuracy of the duct model are included.
William A. Miller, Oak Ridge National Laboratory
Yu (Joe) Huang, White Box Technologies
Ronnen Levinson, Lawrence Berkeley National Laboratory