gft/ttm4hvac
Time Series Forecasting
•
3.1M
•
Updated
•
6
Datasets:
time
stringdate 2019-01-01 00:00:00
2019-12-31 23:45:00
| Outdoor Air Temperature (C)
float64 -13.9
42
| Heating Setpoint (C)
float64 10
23.3
| Cooling Setpoint (C)
float64 22.5
40
| Room Air Temperature (C)
float64 8.77
35
| Outdoor Humidity (%)
float64 3
100
| Wind Speed (m/s)
float64 0
17.5
| Direct Solar Radiation (W/m^2)
float64 0
1.03k
| HVAC Power Consumption (W)
float64 20
871k
| series_id
int64 0
29
| is_default
bool 2
classes |
|---|---|---|---|---|---|---|---|---|---|---|
2019-01-01 00:00:00
| 3.15
| 13.073122
| 24.270164
| 18.945633
| 93
| 0.65
| 0
| 96.85838
| 0
| false
|
2019-01-01 00:15:00
| 4.075
| 12
| 24.921984
| 18.855467
| 93.5
| 0.325
| 0
| 127.47386
| 0
| false
|
2019-01-01 00:30:00
| 5
| 12
| 24.870577
| 18.773378
| 94
| 0
| 0
| 156.1336
| 0
| false
|
2019-01-01 00:45:00
| 5.125
| 13.246161
| 24.631392
| 18.69623
| 93.75
| 0
| 0
| 183.73726
| 0
| false
|
2019-01-01 01:00:00
| 5.25
| 13.090104
| 25.185616
| 18.624104
| 93.5
| 0
| 0
| 209.07198
| 0
| false
|
2019-01-01 01:15:00
| 5.375
| 12.161638
| 24.742609
| 18.557585
| 93.25
| 0
| 0
| 232.19963
| 0
| false
|
2019-01-01 01:30:00
| 5.5
| 14.671763
| 24.52142
| 18.49672
| 93
| 0
| 0
| 253.11432
| 0
| false
|
2019-01-01 01:45:00
| 5.625
| 13.824336
| 25.024158
| 18.44141
| 93.5
| 0
| 0
| 272.01675
| 0
| false
|
2019-01-01 02:00:00
| 5.75
| 15.717453
| 25.07757
| 18.390991
| 94
| 0
| 0
| 289.03534
| 0
| false
|
2019-01-01 02:15:00
| 5.875
| 15.39276
| 24.990223
| 18.345003
| 94.5
| 0
| 0
| 304.4274
| 0
| false
|
2019-01-01 02:30:00
| 6
| 14.682483
| 25.343355
| 18.303108
| 95
| 0
| 0
| 318.37735
| 0
| false
|
2019-01-01 02:45:00
| 6.125
| 16.79
| 25.999092
| 18.265
| 94.5
| 0
| 0
| 1,623.4508
| 0
| false
|
2019-01-01 03:00:00
| 6.25
| 17.04971
| 26.137924
| 18.231243
| 94
| 0
| 0
| 2,088.7383
| 0
| false
|
2019-01-01 03:15:00
| 6.375
| 13.204674
| 26.310513
| 18.203611
| 93.5
| 0
| 0
| 350.93878
| 0
| false
|
2019-01-01 03:30:00
| 6.5
| 17.010862
| 26.31026
| 18.18395
| 93
| 0
| 0
| 1,766.563
| 0
| false
|
2019-01-01 03:45:00
| 6.625
| 17.07524
| 26.831106
| 18.169542
| 93
| 0
| 0
| 1,329.2971
| 0
| false
|
2019-01-01 04:00:00
| 6.75
| 17.021399
| 26.673302
| 18.159111
| 93
| 0
| 0
| 869.04333
| 0
| false
|
2019-01-01 04:15:00
| 6.875
| 17.766016
| 27.41792
| 18.150164
| 93
| 0
| 0
| 4,578.597
| 0
| false
|
2019-01-01 04:30:00
| 7
| 18.533371
| 28.185274
| 18.533361
| 93
| 0
| 0
| 6,475.0576
| 0
| false
|
2019-01-01 04:45:00
| 6.75
| 19.147133
| 28.799036
| 19.146578
| 94.75
| 0.65
| 0
| 7,184.6436
| 0
| false
|
2019-01-01 05:00:00
| 6.5
| 18.928614
| 28.580517
| 18.93455
| 96.5
| 1.3
| 0
| 3,376.0625
| 0
| false
|
2019-01-01 05:15:00
| 6.25
| 19.247524
| 28.899427
| 19.246853
| 98.25
| 1.95
| 0
| 4,928.2886
| 0
| false
|
2019-01-01 05:30:00
| 6
| 20.024862
| 29.676764
| 19.832493
| 100
| 2.6
| 0
| 9,011.953
| 0
| false
|
2019-01-01 05:45:00
| 6
| 20.817669
| 30
| 20.205215
| 96.75
| 2.6
| 0
| 10,063.938
| 0
| false
|
2019-01-01 06:00:00
| 6
| 21.610882
| 30
| 20.480295
| 93.5
| 2.6
| 0
| 10,504.014
| 0
| false
|
2019-01-01 06:15:00
| 6
| 20.804695
| 30
| 20.717901
| 90.25
| 2.6
| 0
| 6,576.428
| 0
| false
|
2019-01-01 06:30:00
| 6
| 21.592506
| 30
| 20.931482
| 87
| 2.6
| 0
| 10,017.439
| 0
| false
|
2019-01-01 06:45:00
| 5.75
| 22.118565
| 30
| 21.102388
| 88.5
| 2.6
| 0
| 9,556.149
| 0
| false
|
2019-01-01 07:00:00
| 5.5
| 22.399586
| 30
| 21.228981
| 90
| 2.6
| 0
| 10,543.593
| 0
| false
|
2019-01-01 07:15:00
| 5.25
| 22.198702
| 30
| 21.382452
| 91.5
| 2.6
| 0
| 8,765.484
| 0
| false
|
2019-01-01 07:30:00
| 5
| 21.975185
| 30
| 21.524256
| 93
| 2.6
| 0
| 8,368.487
| 0
| false
|
2019-01-01 07:45:00
| 4.75
| 21.731304
| 30
| 22.235714
| 93
| 2.6
| 151.5
| 2,054.8079
| 0
| false
|
2019-01-01 08:00:00
| 4.5
| 21.071203
| 30
| 22.825392
| 93
| 2.6
| 202
| 791.38904
| 0
| false
|
2019-01-01 08:15:00
| 4.25
| 21.92029
| 30
| 23.274126
| 93
| 2.6
| 274
| 1,677.7026
| 0
| false
|
2019-01-01 08:30:00
| 4
| 22.191889
| 30
| 23.635902
| 93
| 2.6
| 346
| 1,328.2281
| 0
| false
|
2019-01-01 08:45:00
| 4
| 21.251463
| 30
| 24.485989
| 93
| 2.6
| 418
| 746.63446
| 0
| false
|
2019-01-01 09:00:00
| 4
| 21.018179
| 30
| 25.043379
| 93
| 2.6
| 490
| 715.2446
| 0
| false
|
2019-01-01 09:15:00
| 4
| 21.403366
| 30
| 25.46417
| 93
| 2.6
| 497
| 697.3201
| 0
| false
|
2019-01-01 09:30:00
| 4
| 21.800327
| 30
| 25.826168
| 93
| 2.6
| 504
| 861.47046
| 0
| false
|
2019-01-01 09:45:00
| 4
| 22.451347
| 30
| 26.207481
| 91.5
| 2.6
| 511
| 891.62286
| 0
| false
|
2019-01-01 10:00:00
| 4
| 23.158234
| 30
| 26.574219
| 90
| 2.6
| 518
| 878.8556
| 0
| false
|
2019-01-01 10:15:00
| 4
| 23.25
| 30
| 26.883717
| 88.5
| 2.6
| 511.25
| 835.93726
| 0
| false
|
2019-01-01 10:30:00
| 4
| 23.25
| 30
| 27.193907
| 87
| 2.6
| 504.5
| 778.1747
| 0
| false
|
2019-01-01 10:45:00
| 3.75
| 23.25
| 30
| 27.324364
| 88.5
| 2.6
| 497.75
| 731.5506
| 0
| false
|
2019-01-01 11:00:00
| 3.5
| 23.25
| 30
| 27.512352
| 90
| 2.6
| 491
| 700.33295
| 0
| false
|
2019-01-01 11:15:00
| 3.25
| 23.25
| 30
| 27.698118
| 91.5
| 2.6
| 454.75
| 638.76733
| 0
| false
|
2019-01-01 11:30:00
| 3
| 23.25
| 30
| 27.896685
| 93
| 2.6
| 418.5
| 583.04175
| 0
| false
|
2019-01-01 11:45:00
| 3
| 23.25
| 30
| 27.845217
| 91.5
| 2.85
| 382.25
| 545.74414
| 0
| false
|
2019-01-01 12:00:00
| 3
| 23.25
| 30
| 27.807064
| 90
| 3.1
| 346
| 539.79
| 0
| false
|
2019-01-01 12:15:00
| 3
| 23.25
| 30
| 27.817747
| 88.5
| 3.35
| 330.25
| 474.1019
| 0
| false
|
2019-01-01 12:30:00
| 3
| 23.25
| 30
| 27.85832
| 87
| 3.6
| 314.5
| 453.4151
| 0
| false
|
2019-01-01 12:45:00
| 3
| 23.25
| 30
| 28.08262
| 87
| 3.35
| 298.75
| 471.6411
| 0
| false
|
2019-01-01 13:00:00
| 3
| 23.25
| 30
| 28.32049
| 87
| 3.1
| 283
| 457.8376
| 0
| false
|
2019-01-01 13:15:00
| 3
| 23.25
| 30
| 28.497484
| 87
| 2.85
| 283.75
| 443.53635
| 0
| false
|
2019-01-01 13:30:00
| 3
| 23.25
| 30
| 28.639027
| 87
| 2.6
| 284.5
| 433.68396
| 0
| false
|
2019-01-01 13:45:00
| 3
| 23.25
| 30
| 28.78445
| 87
| 2.975
| 285.25
| 419.47955
| 0
| false
|
2019-01-01 14:00:00
| 3
| 23.25
| 30
| 28.911966
| 87
| 3.35
| 286
| 396.45874
| 0
| false
|
2019-01-01 14:15:00
| 3
| 23.25
| 30
| 29.014353
| 87
| 3.725
| 271.75
| 363.84708
| 0
| false
|
2019-01-01 14:30:00
| 3
| 23.25
| 30
| 29.09517
| 87
| 4.1
| 257.5
| 332.2456
| 0
| false
|
2019-01-01 14:45:00
| 3.25
| 23.25
| 30
| 29.109053
| 82.5
| 3.85
| 243.25
| 274.95288
| 0
| false
|
2019-01-01 15:00:00
| 3.5
| 23.25
| 30
| 29.12635
| 78
| 3.6
| 229
| 227.41246
| 0
| false
|
2019-01-01 15:15:00
| 3.75
| 23.25
| 30
| 29.164557
| 73.5
| 3.35
| 171.75
| 167.44286
| 0
| false
|
2019-01-01 15:30:00
| 4
| 23.25
| 30
| 29.208403
| 69
| 3.1
| 114.5
| 110.664375
| 0
| false
|
2019-01-01 15:45:00
| 3.75
| 23.25
| 30
| 29.042831
| 70.25
| 3.35
| 57.25
| 94.49068
| 0
| false
|
2019-01-01 16:00:00
| 3.5
| 23.25
| 30
| 28.916416
| 71.5
| 3.6
| 0
| 111.31481
| 0
| false
|
2019-01-01 16:15:00
| 3.25
| 23.25
| 30
| 28.80172
| 72.75
| 3.85
| 0
| 130.16916
| 0
| false
|
2019-01-01 16:30:00
| 3
| 23.25
| 30
| 28.693161
| 74
| 4.1
| 0
| 147.62169
| 0
| false
|
2019-01-01 16:45:00
| 3
| 23.25
| 30
| 28.588377
| 74
| 3.975
| 0
| 152.92947
| 0
| false
|
2019-01-01 17:00:00
| 3
| 23.25
| 30
| 28.49062
| 74
| 3.85
| 0
| 159.28514
| 0
| false
|
2019-01-01 17:15:00
| 3
| 23.25
| 30
| 28.396233
| 74
| 3.725
| 0
| 166.6213
| 0
| false
|
2019-01-01 17:30:00
| 3
| 23.25
| 30
| 28.32594
| 74
| 3.6
| 0
| 169.15137
| 0
| false
|
2019-01-01 17:45:00
| 2.85
| 23.25
| 30
| 27.251715
| 76.25
| 3.6
| 0
| 822.83325
| 0
| false
|
2019-01-01 18:00:00
| 2.7
| 23.25
| 30
| 26.572493
| 78.5
| 3.6
| 0
| 810.24554
| 0
| false
|
2019-01-01 18:15:00
| 2.55
| 23.25
| 30
| 26.193127
| 80.75
| 3.6
| 0
| 813.9868
| 0
| false
|
2019-01-01 18:30:00
| 2.4
| 23.25
| 30
| 25.834457
| 83
| 3.6
| 0
| 998.9287
| 0
| false
|
2019-01-01 18:45:00
| 2.3
| 23.25
| 30
| 25.252714
| 85.5
| 3.6
| 0
| 2,331.8633
| 0
| false
|
2019-01-01 19:00:00
| 2.2
| 23.25
| 30
| 24.720537
| 88
| 3.6
| 0
| 2,967.4714
| 0
| false
|
2019-01-01 19:15:00
| 2.1
| 23.25
| 30
| 24.323812
| 90.5
| 3.6
| 0
| 3,546.933
| 0
| false
|
2019-01-01 19:30:00
| 2
| 23.25
| 30
| 23.975569
| 93
| 3.6
| 0
| 3,949.9011
| 0
| false
|
2019-01-01 19:45:00
| 1.75
| 23.25
| 30
| 23.464931
| 91.25
| 2.7
| 0
| 4,927.514
| 0
| false
|
2019-01-01 20:00:00
| 1.5
| 23.25
| 30
| 23.250605
| 89.5
| 1.8
| 0
| 5,728.3394
| 0
| false
|
2019-01-01 20:15:00
| 1.25
| 23.25
| 30
| 23.250717
| 87.75
| 0.9
| 0
| 6,104.211
| 0
| false
|
2019-01-01 20:30:00
| 1
| 23.25
| 30
| 23.25057
| 86
| 0
| 0
| 6,163.896
| 0
| false
|
2019-01-01 20:45:00
| 1
| 21.843977
| 27.800735
| 22.611824
| 87.75
| 0.525
| 0
| 1,318.2935
| 0
| false
|
2019-01-01 21:00:00
| 1
| 22.298067
| 28.338272
| 22.302696
| 89.5
| 1.05
| 0
| 3,761.1868
| 0
| false
|
2019-01-01 21:15:00
| 1
| 20.938759
| 28.339098
| 21.928207
| 91.25
| 1.575
| 0
| 1,521.0049
| 0
| false
|
2019-01-01 21:30:00
| 1
| 21.577145
| 29.259836
| 21.626223
| 93
| 2.1
| 0
| 3,108.776
| 0
| false
|
2019-01-01 21:45:00
| 1
| 23.25
| 29.137383
| 22.78696
| 93
| 1.95
| 0
| 11,524.268
| 0
| false
|
2019-01-01 22:00:00
| 1
| 22.549349
| 27.030676
| 22.549824
| 93
| 1.8
| 0
| 8,155.915
| 0
| false
|
2019-01-01 22:15:00
| 1
| 22.049068
| 28.507315
| 22.051964
| 93
| 1.65
| 0
| 6,697.8403
| 0
| false
|
2019-01-01 22:30:00
| 1
| 22.432087
| 27.85673
| 22.429697
| 93
| 1.5
| 0
| 7,190.94
| 0
| false
|
2019-01-01 22:45:00
| 1.075
| 23.058992
| 27.142178
| 22.711283
| 92.75
| 1.45
| 0
| 10,219.878
| 0
| false
|
2019-01-01 23:00:00
| 1.15
| 23.25
| 27.055677
| 22.814093
| 92.5
| 1.4
| 0
| 9,617.074
| 0
| false
|
2019-01-01 23:15:00
| 1.225
| 22.902735
| 26.972658
| 22.903093
| 92.25
| 1.35
| 0
| 9,033.175
| 0
| false
|
2019-01-01 23:30:00
| 1.3
| 23.25
| 27.153954
| 22.969507
| 92
| 1.3
| 0
| 8,856.548
| 0
| false
|
2019-01-01 23:45:00
| 1.35
| 23.25
| 26.69425
| 23.009148
| 91.75
| 1.225
| 0
| 8,709.563
| 0
| false
|
2019-01-02 00:00:00
| 1.4
| 23.25
| 27.297716
| 23.054245
| 91.5
| 1.15
| 0
| 9,153.772
| 0
| false
|
2019-01-02 00:15:00
| 1.45
| 22.237074
| 26.34109
| 22.237215
| 91.25
| 1.075
| 0
| 4,477.5615
| 0
| false
|
2019-01-02 00:30:00
| 1.5
| 22.58504
| 26.357935
| 22.428831
| 91
| 1
| 0
| 9,495.143
| 0
| false
|
2019-01-02 00:45:00
| 1.475
| 22.183752
| 26.520432
| 22.184168
| 91.25
| 0.95
| 0
| 7,130.0864
| 0
| false
|
End of preview. Expand
in Data Studio
TTM4HVAC – Training dataset (source-all)
This dataset contains HVAC and weather time-series data used to train the source-all TinyTimeMixer model (gft/ttm4hvac), the main model of the TTM4HVAC project.
It aggregates all available source-building data under default and non-default conditions.
Check out the paper arXiv:XXXX.XXXXX (to be released) and visit the main repository ttm4hvac for further details.
Columns
timeOutdoor 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_idis_default
Usage
from datasets import load_dataset
ds = load_dataset("gft/ttm4hvac-source-all-train")
df = ds["train"].to_pandas()
✒️ Citation
If you use this model or datasets, please cite:
**F. Aran**,
*Transfer learning of building dynamics digital twin for HVAC control with Time-series Foundation Model*,
arXiv:XXXX.XXXXX, 2025.
https://arxiv.org/abs/XXXX.XXXXX
- Downloads last month
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Size of downloaded dataset files:
25.4 MB
Size of the auto-converted Parquet files:
25.4 MB
Number of rows:
1,051,200
Models trained or fine-tuned on gft/ttm4hvac-source-all-train