2241. Agent-based building stock modeling incorporating behavioural economics applied to heat grid planning
Invited abstract in session WC-44: Improving data and methods for energy system investment, stream Energy Economics & Management.
Wednesday, 12:30-14:00Room: Newlyn 1.01
Authors (first author is the speaker)
| 1. | Thilo Glißmann
|
| Department for Energy Economics and System Analysis, Fraunhofer IEE, Fraunhofer Institute for Energy Economics and Energy System Technology | |
| 2. | Helen Ganal
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| Department for Energy Economics and System Analysis, Fraunhofer IEE, Fraunhofer Institute for Energy Economics and Energy System Technology | |
| 3. | Sarah Becker
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| Department for Energy Economics and System Analysis, Fraunhofer IEE, Fraunhofer Institute for Energy Economics and Energy System Technology | |
| 4. | Sascha Holzhauer
|
| University of Kassel/Fraunhofer IEE, Fraunhofer Institute for Energy Economics and Energy System Technology |
Abstract
The evolution of the building stock is crucial for energy infrastructure planning, particularly concerning heat grids, which are essential to efficient, climate-neutral heat supply. However, the diversity of building types, uncertainties regarding current refurbishment status and heating system, and owner-specific motivations make reliable forecasting challenging.
We introduce AgentHomeID, an agent-based model of the German building stock, wherein building owner agents make all energy-related decisions. Refurbishment considerations are triggered by regulatory, technical, and personal factors. Options include measures for the building envelope and heating system, influenced by regulation, technical constraints, and infrastructure. Decisions rely on evaluations of costs, subsidies, energy performance, emissions, and measure type. The agents are categorised into private owners, whose choices reflect empirically derived heterogeneous willingness-to-pay, and institutional owners, who evaluate options based on net present value, utilising owner-subclass dependent discount factors and revenue streams.
AgentHomeID is applied within the context of district heating planning. By simulating owner decisions on adopting district heating, we estimate the share of connected buildings as a measure of grid profitability. We identify poorly insulated buildings that pose challenges to reducing grid supply temperatures which facilitate the integration of renewable energy sources into the grid.
Keywords
- Agent Systems
- Behavioural OR
- Energy Policy and Planning
Status: accepted
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