| Summary: In this study, the new method is proposed to estimate heating and cooling loads of residential buildings according to residential building design parameters such as building geometry and physical properties of building envelope. The aim of this method is determined the effects of residential building design parameters to heating and cooling loads, calculated easy and short time heating and cooling loads of residential buildings by means of statictical models based on improved regression formulations according to selected parameter values in residential building design phase and determined residential building design parameters that present optimum solution in terms of energy saving for Turkish Climate Regions. In this study, annual heating and cooling loads of residential building models with one storey, mid-storey and high storey - floor area of 100 square meter having twelve different building shape factor are calculated by means of EnergyPlus simulation program according to four building orientation, three window-wall ratio, four glazing type and three wall construction alternatives in thirteen city in five climate region represented Geographical Regions in Turkey. ASHRAE Heat Balance Method is used in calculations. Regression formulations based on building shape factor, window-wall ratio, heat transfer coefficient of window and wall construction (U- W/m2K), solar heat gain coefficient (SHGC) and area of window and wall construction are created by means of SPSS program using heating and cooling load values obtained to thirteen city. Besides, value intervals of residential building design parameters presented optimum solution in terms of energy saving are determined by means of cluster analysis using simulation results in thirteen city. This thesis study is including four section that are General Information, Practice Studies, Findings and Discussion and Results and Suggestions. In the first section, studies about the main problem in literature is investigated and general information is given related to estimation heating and cooling load of buildings. In the second section, results obtained according to climate regions are presented as graphical, created regression formulations are explained elaborately. In the third section, obtained results are interpreted and compared to previous studies in literature. In the final section, general results of this study are given and suggestions are presented to researchers for future studies.
Key Words: Heating load, Cooling load, EnergyPlus, Regression analysis, Cluster analysis, Orientation, Building geometry, Physical properties of building envelope
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