Early design phase decisions can be critically important to the energy impact of a building. Building orientation and exterior aesthetics which drive window sizes and types are often made by architects and owners prior to the involvement of any daylighting or sustainability consultants. Because these designs can be difficult, if not impossible, to change as the design process proceeds the need to inform and educate these decisions has led through this research to the development of a set of EnergyPlus based regression equations capable of predicting annual lighting, cooling and heating loads of a private office design with minimal input. The ability to evaluate the impact of these three main energy consumption sources provides a complete picture of the consequences of design decisions that most other early design phase methods do not achieve. A test case using these equations calculated to within 4% to 8% of EnergyPlus simulation results.

The development of the regression equations began with a validation study of four daylighting programs: EnergyPlus Detailed, EnergyPlus DELight, DAYSIM, and SPOT. Full scale daylighting measurements recorded in an empty private office in Ottawa, Ontario by the National Research Council of Canada provided data to validate the daylighting software against with EnergyPlus Detailed method selected for its accuracy and runtime. EnergyPlus was then used to perform parametric simulations of various building design parameters from which the regression formulas are created. These formulas are produced for four US cities of varying climates to confirm the regression approach is transferable.