The development of a simplified algebraic expression that can be used to predict the effects ofsvarious window parameters on residential energy use is documented. A comprehensive parametric study of asprototypical single-family ranch-style house was performed using the DOE-2.1B energy analysis simulationsprogram. The data base generated for the study consisted of the heating, cooling, and total energy requirementssand subsequent costs due to changes in the fenestration characteristics of orientation, size, conductance,sand shading coefficient. Incremental effects due to shade management, night insulation, andsoverhangs were also part of the data base. Climate sensitivity was established by considering results fromsfour geographic locations representative of the climate extremes in the continental U.S. Multiple regressionstechniques were used to generate a simplified algebraic expression that relates energy use to thesparameters varied. This representation could form the basis for a simplified design tool for selectingsoptimal fenestration parameters.
BT - CLIMA 2000, World Conference on Heating, Ventilation, and Air-Conditioning C1 -Windows and Daylighting Group
C2 - LBL-19245R CN - LBL-19245 Rev. CY - Copenhagen, Denmark DA - 08/1985 LA - eng N2 -The development of a simplified algebraic expression that can be used to predict the effects ofsvarious window parameters on residential energy use is documented. A comprehensive parametric study of asprototypical single-family ranch-style house was performed using the DOE-2.1B energy analysis simulationsprogram. The data base generated for the study consisted of the heating, cooling, and total energy requirementssand subsequent costs due to changes in the fenestration characteristics of orientation, size, conductance,sand shading coefficient. Incremental effects due to shade management, night insulation, andsoverhangs were also part of the data base. Climate sensitivity was established by considering results fromsfour geographic locations representative of the climate extremes in the continental U.S. Multiple regressionstechniques were used to generate a simplified algebraic expression that relates energy use to thesparameters varied. This representation could form the basis for a simplified design tool for selectingsoptimal fenestration parameters.
PP - Copenhagen, Denmark PY - 1985 T2 - CLIMA 2000, World Conference on Heating, Ventilation, and Air-Conditioning T3 - CLIMA 2000, World Conference on Heating, Ventilation, and Air-Conditioning TI - Residential Window Performance Analysis Using Regression Procedures ER -