Register now After registration you will be able to apply for this opportunity online.
Time series analysis - the behavioral patterns of occupants as room temperatures change for more efficient heating systems
As Europe moves towards a renewable energy future, heat pumps are becoming essential in reducing fossil fuel dependency in building heating. Although heat pumps are generally more efficient than traditional combustion-based systems, the high cost of electricity in Europe makes it essential to optimize their operation for affordability.
Heat pump efficiency is closely linked to the amount of energy and power required to maintain comfortable indoor temperatures, which vary significantly by user preferences and building specifics. Strategies such as temperature setbacks—reducing heating when the building is unoccupied or at night—can greatly enhance efficiency. However, applying these strategies effectively requires a nuanced understanding of user-specific comfort ranges and sensitivity to temperature changes.
Keywords: time series analysis, behavior pattern recognition, efficient heating systems
Not specified
This thesis aims to identify and validate new patterns of resident behavior based on operational data from 2,000 heat pumps, supplemented by publicly available datasets. By analyzing set temperatures, changes over time, and actual temperature data, this study will categorize behavioral patterns and statistically evaluate their impact on energy consumption. The goal is to contribute to more precise and user-adaptive heat pump configurations that optimize energy efficiency without sacrificing comfort.
This thesis aims to identify and validate new patterns of resident behavior based on operational data from 2,000 heat pumps, supplemented by publicly available datasets. By analyzing set temperatures, changes over time, and actual temperature data, this study will categorize behavioral patterns and statistically evaluate their impact on energy consumption. The goal is to contribute to more precise and user-adaptive heat pump configurations that optimize energy efficiency without sacrificing comfort.
Ugne Potthoff | PhD Candidate and Research Assistant
ETH Zurich | Bosch IoT Lab | Weinbergstrasse 56/58 | 8092 Zurich | Switzerland
University St. Gallen | Bosch IoT Lab | Dufourstrasse 40a | 9000 St. Gallen | Switzerland
Internet www.iot-lab.ch
Ugne Potthoff | PhD Candidate and Research Assistant ETH Zurich | Bosch IoT Lab | Weinbergstrasse 56/58 | 8092 Zurich | Switzerland University St. Gallen | Bosch IoT Lab | Dufourstrasse 40a | 9000 St. Gallen | Switzerland Internet www.iot-lab.ch
Resident behavior patterns for efficient heating systems.pdf
