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| Thermal Profiling of Residential Energy Consumption for Heat Pump and District Heating Customers |
| Keywords | interesting pattern discovery, energy optimization, data mining, machine learning + |
|---|---|
| Level | Master + |
| OneLineSummary | Finding interesting patterns of heat pump and district heating customers in order to identify meaningful thermal profiles + |
| Prerequisites | Artificial Intelligence and Learning Systems courses; good knowledge of data mining; programming skills for implementing machine learning algorithms + |
| References | H. Gadd and S. Werner, "Heat load patterns … H. Gadd and S. Werner, "Heat load patterns in district heating substations", Applied Energy, vol. 108, pp. 176-183, 2013. A. Albert and R. Rajagopal, "Thermal Profiling of Residential Energy Use", IEEE Transactions on Power Systems, vol. 30, no. 2, pp. 602-611, 2015. A. Albert and R. Rajagopal, "Building dynamic thermal profiles of energy consumption for individuals and neighborhoods", 2013 IEEE International Conference on Big Data, 2013.nternational Conference on Big Data, 2013. |
| StudentProjectStatus | Open + |
| Supervisors | Ece Calikus + , Sławomir Nowaczyk + |
| Title | Thermal Profiling of Residential Energy Consumption for Heat Pump and District Heating Customers + |
| Categories | StudentProject + |
| Modification dateThis property is a special property in this wiki. | 27 September 2017 21:04:06 + |
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