| dc.description.abstract | The Directive 2002/91/EC of the European Parliament on the Energy Performance of Buildings obliges EU member states to develop a methodology for the calculation of the energy performance of buildings on the basis of a framework listed in Appendix A of the document. In Germany, the DIN V 18599 Series of Standards has been developed as the standardized methodology for the calculation of the energy performance of buildings. The complexity of this Series of Standards has led to calls within the German academic community to simplify the process of adhering to this methodology. It is for this reason that Dr.-Ing. Markus Lichtmeß has developed an Excel tool named EnerCalC to simplify the energy performance calculation process whilst ensuring compliance with DIN V 18599.
Hospitals are one of the categories of buildings identified in Directive 2002/91/EC for which an energy performance calculation methodology must be developed. This thesis focuses on using EnerCalC to calculate the energy performance of buildings O.10, S.50, and O.70 at the University Medical Center Hamburg Eppendorf, a complex hospital located in Hamburg, Germany. A significant part of this thesis is concerned a sensitivity and interdependency analysis of the building parameters given in EnerCalC so as to establish the most relevant real world data inputs required to carry out the energy performance analysis of a hospital building.
The sensitivity and interdependency analyses identified the most relevant parameters by inputting a defined sensitivity range into a reference building on a one-factor-at-a-time basis, and by investigating the interdependency of the net energy values output using a Pearson Chi Square Test. Finding the most relevant parameters in EnerCalC in this manner significantly reduces the real world data requirements when modeling the energy performance of a building using EnerCalC. Given EnerCalC's compliance DIN V 18599, this allows for reduced real world data requirements when modeling the energy performance of any building, not just hospital buildings.
A zoning procedure and the collection of building parameter data of buildings O.10, S.50, and O.70 followed the sensitivity and interdependency analyses. The total heating values of the three buildings were modeled with an accuracy between 63% and 103%. The difficulty of gathering data on the other utilities led to only S.50's energy performance being fully modeled, with cooling, lighting, and ventilation being modeled with an accuracy of 50%, 98%, and 47%, respectively. | |
