Research Collection Master Thesis Georeferenced modelling of residential heat demand in Appenzell Ausserrhoden Author(s): Schlegel, Matthias Publication Date: 2010-08 Permanent Link: https://doi.org/10.3929/ethz-a-007083287 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library NSSI Master Thesis 05/10 August 2010 Georeferenced modelling of residential heat demand in Appenzell Ausserrhoden Matthias Schlegel Supervisors: Prof. Dr. Roland W. Scholz Hans Bruderer Dr. Justus Gallati Evelina Trutnevyte Space heating Hot water demand demand • Specific hot water • Specific space heating demand demand • Number of inhabitants • Energy reference area Total heat demand IED – Institute for Environmental Decisions NSSI – Natural and Social Science Interface Georeferenced modelling of residential heat demand in Appenzell Ausserrhoden Matthias Schlegel Geissfluhweg 24 4600 Olten 1 Introduction ................................................................................................................................................................. 19 2 Methodology .............................................................................................................................................................. 29 3 Results ............................................................................................................................................................................. 71 4 Discussion .................................................................................................................................................................... 115 5 Conclusion .................................................................................................................................................................. 139 August 2010 1 Matthias Schlegel Georeferenced modelling of residential heat demand in Appenzell Ausserrhoden 2 NSSI Master Thesis 05/10 Abstract Under the threat of climate change and increasing dependence on fossil energy imports, a transi- tion of the energy system seems vital. Peripheral regions are especially challenged due to bad pre- conditions in form of a dispersed, old building stock and small economic power, but also dispose of the advantage of high renewable energy potentials. To support authorities faced by these issues, a decision support system for energy-related policy is indispensable. As a first, sound foundation for it, and to apply the corresponding methodology to a rural setting in an elaborate way, a spatially explicit model of residential heat demand on the level of individual building was established for the Swiss canton of Appenzell Ausserrhoden (AR). The aim was also to go beyond simple engineer- ing perspectives when harvesting the wealth of generated information. A proven approach for the evaluation of space heating and hot water demand was applied, using energy reference area and inhabitant numbers as demand indicators as well as the corresponding specific demand coeffi- cients, however accompanied by extensive data processing and inclusion of additional external factors. To prepare the ground for further extensions of the model, this was followed up with wide-ranging conceptual considerations about relevant factors for modelling building stock trans- formation. The total modelled residential heat demand for the canton of AR in 2010 amounts to 1’576 TJ/y as useful energy. It is concentrated in the centres of the villages not just because of dense settlement but also due to above-average specific heat demand, which was explained by a series of differing energy-related building characteristics in the dispersed settlements, where wood stove heating is predominant. Accordingly, a high refurbishment potential and a low degree of sustainability in terms of energy equity as well as energy dependence and environmental impact was identified in the villages, calling for action. The big effort required for the model creation is deemed worth- while, since it allows for various applications ranging from engineering optimisation of energy supply systems to design of policy measures by iterative effect appraisal, and the model is easily transferrable to other regions within Switzerland. Future research is recommended to extend the georeferenced decision support system by coupling the heat demand model with a model for the supply side covering especially local renewable energy potentials, in order to allow considerations about optimal resource allocation and potential sustainability of the energy system. Keywords Residential heat demand model, GIS, decision support system, building stock transformation August 2010 3 Matthias Schlegel Georeferenced modelling of residential heat demand in Appenzell Ausserrhoden 4 NSSI Master Thesis 05/10 Table of contents Figures .......................................................................................................................................................................................... 9 Tables ........................................................................................................................................................................................... 13 Acronyms and Abbreviations ............................................................................................................................................. 15 Variables and Units ............................................................................................................................................................... 16 Glossary ....................................................................................................................................................................................... 17 1 Introduction ........................................................................................................................................... 19 1.1 Background and problem definition ..................................................................................................... 19 1.2 Research framework .................................................................................................................................... 22 1.3 Study area ......................................................................................................................................................... 25 2 Methodology ......................................................................................................................................... 29 2.1 Source data ..................................................................................................................................................... 29 2.1.1 Data collection and description ................................................................................................. 29 2.1.1.1 National Register of Buildings and Dwellings ......................................................... 31 2.1.1.2 Specific space heating demand coefficients ............................................................ 32 2.1.1.3 Demand indicator and coefficients for hot water use ........................................ 34 2.1.1.4 Additional data ...................................................................................................................... 37 2.1.1.5 GIS layers ................................................................................................................................. 39 2.1.2 Data processing ................................................................................................................................ 39 2.1.2.1 National Register of Buildings and Dwellings ........................................................ 42 2.1.2.2 Specific space heating demand coefficients ........................................................... 46 2.1.2.3 Other data .............................................................................................................................. 49 2.2 Heat demand model ..................................................................................................................................... 51 2.2.1 Space heating demand .................................................................................................................. 52 2.2.1.1 Energy reference area ......................................................................................................... 52 2.2.1.2 Specific space heating demand ..................................................................................... 53 2.2.2 Hot water demand .......................................................................................................................... 56 2.2.3 Total residential heat demand .................................................................................................... 58 2.2.3.1 Aggregation to useful and final energy ..................................................................... 58 2.2.3.2 Further analysis of the results ....................................................................................... 59 2.2.3.3 Validation and sensitivity analysis of the results .................................................. 63 2.3 Data description and visualisation ....................................................................................................... 67 2.3.1 Descriptive visualisation of the heat supply and demand