Building energy simulation has become a useful tool for predicting cooling, heating and electrical loads for facilities. Simulation models have been validated throughout the years by comparing simulation results to actual measured values. The simulations have become more accurate as approaches were changed to be more comprehensive in their ability to model building features. These simulation models tend to require considerable experience in determining input parameters and large amounts of time to construct the models. As a result of the large number of man-hours required, simplified models have been sought and used. Simplified models are particularly useful for conducting preliminary assessments of energy conservation measures. These simplified models often use linear relationships in order to estimate conditions such as infiltration, energy usage, and temperature gradients. Studies have been performed in order to validate popular models such as ASHRAE's Bin or Modified Bin methods. A useful measure would be to determine the accuracy of a simplified model to establish error bounds. Having a simplified model and establishing its error bounds, technical estimations from such models could be used in selected applications with more confidence. The error bound relative to DOE-2 predictions, for a proposed simplified model denoted IEC, for estimating a commercial building's cooling load are presented along with two actual-building test cases for validation purposes. The sensitivity of the error to various building parameters such as minimum make-up air, cooling capacity oversize, and internal equipment load was investigated. The error bound was determined to be within ±15 per cent for both cases and almost all variations. / Master of Science

<p>The impact of window area on the energy balance of a building was investigated by simulations in DEROB-LTH. The glazed area was varied in three types of buildings with different types of glazing and for several climates.</p><p>One low energy house was compared to a less insulated house but identical in size and layout. Three different types of glazing were used; uncoated double glazing, double glazing with one low-e coated pane and triple glazing with two low-e coated panes. Climates with variations in solar radiation, mean temperature, altitude and latitude were chosen.</p><p>The results show that if energy efficient window alternatives are chosen the flexibility of choosing the glazed area and orientation is higher. Choosing a larger area facing south resulted in a higher heating demand for uncoated double glazing in the standard house. An increased area also resulted in an increased peak load for heating for all the simulated cases. Choosing the energy efficient glazing type gave a decrease in heating demand for increased south facing glazed area in the standard house. In the low energy house the difference in heating demand between different areas was smaller than for the standard house. </p><p>An office module with two types of switchable glazing and one solar control glazing unit was used in three different climates; Stockholm, Brussels and Rome. Larger window areas increase the cooling demand but if glazing types with lower solar transmittance are used, the difference in cooling demand between different window areas decreases. An extremely large window area, however, increases the peak load both for cooling and for heating and should therefore be avoided. Energy can be saved by using switchable windows instead of solar control or in particular standard glazing.</p>

The impact of window area on the energy balance of a building was investigated by simulations in DEROB-LTH. The glazed area was varied in three types of buildings with different types of glazing and for several climates. One low energy house was compared to a less insulated house but identical in size and layout. Three different types of glazing were used; uncoated double glazing, double glazing with one low-e coated pane and triple glazing with two low-e coated panes. Climates with variations in solar radiation, mean temperature, altitude and latitude were chosen. The results show that if energy efficient window alternatives are chosen the flexibility of choosing the glazed area and orientation is higher. Choosing a larger area facing south resulted in a higher heating demand for uncoated double glazing in the standard house. An increased area also resulted in an increased peak load for heating for all the simulated cases. Choosing the energy efficient glazing type gave a decrease in heating demand for increased south facing glazed area in the standard house. In the low energy house the difference in heating demand between different areas was smaller than for the standard house. An office module with two types of switchable glazing and one solar control glazing unit was used in three different climates; Stockholm, Brussels and Rome. Larger window areas increase the cooling demand but if glazing types with lower solar transmittance are used, the difference in cooling demand between different window areas decreases. An extremely large window area, however, increases the peak load both for cooling and for heating and should therefore be avoided. Energy can be saved by using switchable windows instead of solar control or in particular standard glazing.