Master's Thesis Yicong Pang


Development of a general user profile generator based on existing tools and algorithms

Around 26% of the energy in Germany was consumed by residential building sector and private households spent 69 billion euros on electricity, gas and other energy source in 2014 [DENA, 2014]. Apart from weather conditions and building type, energy-related occupants’ behavior also has a major impact on the energy use in buildings. In order to accurately predict residential energy demand, it is important to develop a user profile generator, which can simulate the presence of occupants and their behavior in dealing with building technology.

This thesis aims to evaluate the various existing individual profile generators. Through comparison and analysis their strengths and weaknesses, the most appropriate ones are selected and then combined into a user profile generator. The proposed generator is able to generate energy demand profiles at the individual household level, which consists of occupancy profiles, electricity demand and thermal demand.

Five groups of profile generators are evaluated in this thesis. They generate profiles for occupancy, electric appliance load, lighting load, domestic hot water demand and space heating demand. The generators of the same group are compared to each other. The results are validated with different reference data. Meanwhile, by analyzing the approach, the database and the performance of the generators, adjustments and improvements are done to make them more representative for the households in Germany.

In addition, this thesis also aims to validate a number of factors which affect residential energy demand and the results serve as the reference and recommendation for future work.