Systems analysis of heat supply from wood residues
- Project team:
Biemann, Kirsten (Dissertation)
- Start date:
- End date:
- Research group:
Energy - resources, technologies, systems
According to the BMU study, "Langfristszenarien und Strategien für den Ausbau der erneuerbaren Energien in Deutschland bei Berücksichtigung der Entwicklung in Europa und global" (long-term scenarios and strategies for the expansion of renewable energies in Germany considering the European and the global development) of 2011, in Germany 58% of the final energy demand of 2008 (which corresponds to 40% of the energy related CO2 emissions) were used for supplying heat. According to the study, the three areas: efficiency enhancement (reduction of heat demand and improved industrial and building systems), increased use of CHP (combined heat and power generation) plants, and the development of renewable energies have to be pursued.
One component for an environmentally more friendly heat supply is heat generation from wood residues.
In my work, I use the method of life cycle assessment to examine different semi-centralized heat supply concepts regarding their impacts on the environment and to compare them with central and decentralized concepts. In contrast to most LCA studies so far, here the construction and the operation of the heating networks are also included. The focus is on heat supply from wood residues. Beside the greenhouse gas emissions, additional impact categories like resource utilization and particulate pollution are examined, in order to ensure that a reduction of greenhouse gas emissions will not lead to stronger negative impacts on the environment in other areas.
For this purpose, data from different studies are being evaluated and combined. Frequently, these studies cannot be compared directly for the reason of diverging time-related reference, and differing technological and geographical coverage, and because of different modeling approaches. Their results sometimes differ substantially. For this reason, first a schematic approach is developed that enables a data quality assessment and a comparison of the different LCI studies. From this assessment, a recommendation on how to model the process chains will be derived and implemented.