| --- |
| pretty_name: TTM4HVAC – Training dataset (source-default) |
| tags: |
| - ttm4hvac |
| - hvac |
| - time-series |
| - energy |
| task_categories: |
| - time-series-forecasting |
| license: mit |
| papers: |
| - title: "Transfer learning of building dynamics digital twin for HVAC control with Time-series Foundation Model" |
| url: https://doi.org/10.1016/j.mex.2026.103866 |
| authors: "Ferran Aran Domingo" |
| --- |
| |
| # TTM4HVAC – Training dataset (source-default) |
|
|
| This dataset contains HVAC and weather time-series data collected under **default building control schedules** for the source domain. |
|
|
| It is used to train the `gft/ttm4hvac-source-default` model. |
|
|
| Check out the paper [A reproducible method to generate multi-building, multi-climate HVAC operation datasets with a stochastic exploratory controller](https://doi.org/10.1016/j.mex.2026.103866) and visit the main repository [ttm4hvac](https://huggingface.co/gft/ttm4hvac) for further details. |
|
|
| ## Columns |
|
|
| - `time` |
| - `Outdoor Air Temperature (C)` |
| - `Heating Setpoint (C)` |
| - `Cooling Setpoint (C)` |
| - `Room Air Temperature (C)` |
| - `Outdoor Humidity (%)` |
| - `Wind Speed (m/s)` |
| - `Direct Solar Radiation (W/m^2)` |
| - `HVAC Power Consumption (W)` |
| - `series_id` |
| - `is_default` |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("gft/ttm4hvac-source-default-train") |
| df = ds["train"].to_pandas() |
| df.head() |
| ``` |
|
|
| # ✒️ Citation |
|
|
| If you use this model or datasets, please cite: |
|
|
| ```bibtex |
| @article{aran_domingo_2026_hvac_dataset, |
| title = {A reproducible method to generate multi-building, multi-climate HVAC operation datasets with a stochastic exploratory controller}, |
| author = {Aran Domingo, Ferran and |
| Fraile Alonso, Pablo and |
| Rius Torrentó, Josep and |
| Agost Batalla, Oriol and |
| Barri Vilardell, Ignasi and |
| Vilaplana Mayoral, Jordi and |
| Mateo Fornés, Jordi}, |
| journal = {MethodsX}, |
| volume = {16}, |
| pages = {103866}, |
| year = {2026}, |
| doi = {10.1016/j.mex.2026.103866}, |
| url = {https://doi.org/10.1016/j.mex.2026.103866} |
| } |
| ``` |