Sebastian Burhenne

Sebastian Burhenne, born in 1983,

graduated at the University of Applied Sciences Erfurt in the subject “Building Services Engineering and Energy Technology”. During his studies, he participated in an internship in New Zealand and wrote his Bachelor’s Thesis on the topic “Analysis of Rain Water Harvesting with an Example in a Building Complex in New Zealand”. In August, he received his Bachelor degree with an overall mark of “excellent”. He continued with a Master degree in “Building Services Engineering and Energy Technology”. During his Master’s studies he spent one semester in Newcastle upon Tyne, UK. Sebastian Burhenne was supported by the German National Academic Foundation. He wrote his Master’s Thesis at the Fraunhofer Institute for Solar Energy Systems (ISE) with the topic “Simulation Models to Optimize the Energy Consumption of Buildings”. In November 2008 he graduated with the overall mark of “excellent”.

Abstract of the PhD Thesis: “Bayesian Techniques to Quantify Uncertain Parameters in Building Simulation”

Simulations are often used in the development and planning of renewable energy technologies. The results of the analyses are very useful to design and optimize energy systems. From a modelling perspective, the thermal characteristic of buildings is described with parameters that often can not be estimated with high accuracy. This leads to inaccuracies that cannot be quantified. Quantifying the influence of uncertainties it is possible to increase quality, and number, of inferences that can be derived from the simulations. This increases the accuracy of the planning process and can be useful for the optimization of the building operation.

In this thesis, research will be conducted in order to find the source of uncertainty in building modelling. The uncertainties should be classified, characterized and quantified. Furthermore, the applicability of an a priori probability density functions to simulation parameters is analyzed. In this framework, it is useful to assign a density function to the result of a simulation in order to judge the reliability of the simulation.

A Bayesian approach is used to quantify uncertainty and will be evaluated in the context of thermal building simulations. The basis of the analysis will be existing and simple simulation models. The aim is to develop a model which is able to simulate using probability density functions and hence is able to quantify the uncertainty within the simulation.

The scientific mentoring of the PhD Thesis is provided by Prof. Andreas Wagner (Universität Karlsruhe (TH), Fachgebiet Bauphysik und Technischer Ausbau). The work is accomplished at the Fraunhofer Institute for Solar Energy Systems (ISE) in Freiburg.