Datasets:

gft
/

ttm4hvac-target-cool-test

time stringdate 2019-07-01 00:00:00 2019-07-31 23:45:00	Room Air Temperature (C) float64 19.3 35	Outdoor Air Temperature (C) float64 11 35	Outdoor Humidity (%) float64 0.05 0.97	Direct Solar Radiation (W/m^2) float64 0 923	Wind Speed (m/s) float64 0 12.6	Cooling Setpoint (C) float64 22.5 35	Heating Setpoint (C) float64 10 22.5	HVAC Power Consumption (W) float64 0 2.1k
2019-07-01 00:00:00	20.133651	20.98249	0.389024	0	9.774858	30	15	0
2019-07-01 00:15:00	20.27766	20.677497	0.435107	0	10.148867	30	15	0
2019-07-01 00:30:00	20.295976	20.333753	0.500361	0	10.504075	30	15	0
2019-07-01 00:45:00	20.262584	20.02626	0.554248	0	10.789972	30	15	0
2019-07-01 01:00:00	20.214945	19.803333	0.576331	0	10.853886	30	15	0
2019-07-01 01:15:00	20.165934	19.603333	0.588381	0	10.331113	30	15	0
2019-07-01 01:30:00	20.11524	19.403333	0.598598	0	9.382668	30	15	0
2019-07-01 01:45:00	20.061329	19.203333	0.606667	0	8.313592	30	15	0
2019-07-01 02:00:00	20.002525	19.003333	0.612688	0	7.357193	30	15	0
2019-07-01 02:15:00	19.937433	18.803333	0.618133	0	6.425188	30	15	0
2019-07-01 02:30:00	19.872237	18.603333	0.623255	0	5.48641	30	15	0
2019-07-01 02:45:00	19.809789	18.403333	0.627856	0	4.564329	30	15	0
2019-07-01 03:00:00	19.748681	18.203333	0.631187	0	3.686539	30	15	0
2019-07-01 03:15:00	19.687496	18.003333	0.631504	0	2.880971	30	15	0
2019-07-01 03:30:00	19.625241	17.803333	0.630211	0	2.139477	30	15	0
2019-07-01 03:45:00	19.561121	17.603333	0.629538	0	1.445881	30	15	0
2019-07-01 04:00:00	19.494426	17.403333	0.634427	0	0.810751	30	15	0
2019-07-01 04:15:00	19.426545	17.203333	0.653622	0	0.336988	30	15	0
2019-07-01 04:30:00	19.362179	17.003333	0.678614	3.439861	0.058162	30	15	0
2019-07-01 04:45:00	19.30825	16.803333	0.696581	23.680924	0	30	15	0
2019-07-01 05:00:00	19.272464	16.603333	0.695992	61.409919	0.134305	30	15	0
2019-07-01 05:15:00	19.257597	16.403333	0.677237	113.213051	0.635976	30	15	0
2019-07-01 05:30:00	19.259932	16.203333	0.650776	182.392726	1.273075	30	15	0
2019-07-01 05:45:00	19.269743	16.003333	0.627744	285.513584	1.767904	30	15	0
2019-07-01 06:00:00	19.294833	15.90273	0.617836	403.355531	1.934233	30	15	0
2019-07-01 06:15:00	19.365659	16.2517	0.619327	507.047662	1.979907	30	15	0
2019-07-01 06:30:00	19.505122	16.969307	0.622623	577.196821	2.011093	30	15	0
2019-07-01 06:45:00	19.705868	17.84646	0.61788	633.935974	2.059987	30	15	0
2019-07-01 07:00:00	19.956918	18.709338	0.598975	684.500857	2.148879	30	15	0
2019-07-01 07:15:00	20.255255	19.562254	0.575069	728.110906	2.25841	30	15	0
2019-07-01 07:30:00	20.563868	20.417594	0.549823	765.584395	2.382102	30	15	0
2019-07-01 07:45:00	20.863633	21.266267	0.523692	801.689289	2.521766	30	15	0
2019-07-01 08:00:00	21.881699	22.102733	0.49685	834.10667	2.723597	24	21	3.419666
2019-07-01 08:15:00	22.851159	22.934628	0.468857	858.433541	3.118554	24	21	0
2019-07-01 08:30:00	23.337139	23.76182	0.440608	872.398041	3.595915	24	21	0
2019-07-01 08:45:00	23.723576	24.580738	0.413376	882.119952	3.98041	24	21	0
2019-07-01 09:00:00	24.086854	25.384401	0.389678	889.922691	4.130922	24	21	5.241513
2019-07-01 09:15:00	24.161209	26.150828	0.373782	896.193597	4.091135	24	21	65.572772
2019-07-01 09:30:00	24.048537	26.861273	0.362042	901.49033	3.934786	24	21	110.226616
2019-07-01 09:45:00	24.047207	27.499664	0.348833	906.487407	3.718125	24	21	148.954032
2019-07-01 10:00:00	24.039163	28.065833	0.329794	910.555302	3.455831	24	21	187.814505
2019-07-01 10:15:00	24.034209	28.615833	0.306715	912.760659	3.055397	24	21	224.762612
2019-07-01 10:30:00	24.030168	29.165833	0.281261	911.114707	2.600454	24	21	260.216359
2019-07-01 10:45:00	24.026137	29.715833	0.254266	902.439057	2.22761	24	21	293.314909
2019-07-01 11:00:00	24.022737	30.265833	0.222914	890.794837	2.121398	24	21	323.488173
2019-07-01 11:15:00	24.019933	30.815833	0.177873	882.000558	2.46877	24	21	351.461757
2019-07-01 11:30:00	24.016345	31.365833	0.130486	879.921616	3.034689	24	21	375.26526
2019-07-01 11:45:00	24.014252	31.915833	0.097525	880.135981	3.490422	24	21	396.770828
2019-07-01 12:00:00	24.014313	32.433685	0.088792	880.622569	3.541966	24	21	416.895803
2019-07-01 12:15:00	24.015939	32.803699	0.086292	880.973972	3.211698	24	21	440.5787
2019-07-01 12:30:00	24.015206	33.045237	0.083792	880.905121	2.784663	24	21	464.677598
2019-07-01 12:45:00	24.013742	33.218454	0.081292	880.593212	2.562705	24	21	487.309579
2019-07-01 13:00:00	24.012181	33.376421	0.078711	879.962336	2.750932	24	21	507.941868
2019-07-01 13:15:00	24.010472	33.53047	0.075862	878.820202	3.123864	24	21	526.235025
2019-07-01 13:30:00	24.008671	33.679562	0.073083	875.933193	3.538626	24	21	541.821577
2019-07-01 13:45:00	24.006855	33.825371	0.070844	867.416898	3.926857	24	21	554.501827
2019-07-01 14:00:00	24.005171	33.969037	0.069576	853.861008	4.260977	24	21	564.303451
2019-07-01 14:15:00	24.003747	34.107707	0.069289	837.191484	4.626396	24	21	571.551327
2019-07-01 14:30:00	24.00244	34.23605	0.069557	818.544965	4.949919	24	21	576.521107
2019-07-01 14:45:00	24.00124	34.348708	0.069911	796.674025	5.108502	24	21	579.289296
2019-07-01 15:00:00	23.99991	34.378647	0.07	773.045443	5.039583	24	21	580.009496
2019-07-01 15:15:00	23.997227	34.131861	0.07	750.037982	4.914583	24	21	576.744296
2019-07-01 15:30:00	23.995352	33.733617	0.07	730.568438	4.789583	24	21	569.13537
2019-07-01 15:45:00	23.99617	33.396415	0.07	717.080799	4.664583	24	21	561.670278
2019-07-01 16:00:00	23.998533	33.271803	0.0708	706.378478	4.539583	24	21	557.689205
2019-07-01 16:15:00	24.000194	33.242804	0.075003	694.07845	4.414583	24	21	557.297954
2019-07-01 16:30:00	24.000656	33.249465	0.081354	674.475227	4.289583	24	21	558.376666
2019-07-01 16:45:00	24.000675	33.279528	0.08751	640.30153	4.164583	24	21	559.45636
2019-07-01 17:00:00	24.001172	33.374705	0.089944	593.232852	4.017633	24	21	561.094533
2019-07-01 17:15:00	24.002006	33.667501	0.08469	537.127581	3.779124	24	21	564.268673
2019-07-01 17:30:00	24.001542	33.974335	0.077506	468.748839	3.488603	24	21	567.444119
2019-07-01 17:45:00	23.99895	34.029824	0.076361	369.849512	3.216	24	21	567.336606
2019-07-01 18:00:00	25.889371	33.669677	0.087682	258.181096	3.141001	30	15	18.876898
2019-07-01 18:15:00	27.531714	33.149335	0.108762	161.421521	3.62616	30	15	0
2019-07-01 18:30:00	27.978701	32.58326	0.134104	98.684282	4.388041	30	15	0
2019-07-01 18:45:00	28.080002	31.999901	0.158786	53.408024	4.976374	30	15	0
2019-07-01 19:00:00	28.065139	31.422145	0.179483	20.762364	4.908346	30	15	0
2019-07-01 19:15:00	27.997327	30.846346	0.199087	3.172149	3.960958	30	15	0
2019-07-01 19:30:00	27.902854	30.270365	0.217522	0	2.670162	30	15	0
2019-07-01 19:45:00	27.799753	29.695865	0.233241	0	1.705922	30	15	0
2019-07-01 20:00:00	27.69413	29.124953	0.2439	0	1.533248	30	15	0
2019-07-01 20:15:00	27.5845	28.561668	0.246893	0	1.738196	30	15	0
2019-07-01 20:30:00	27.472871	28.009579	0.246209	0	2.141966	30	15	0
2019-07-01 20:45:00	27.361983	27.4719	0.247331	0	2.73259	30	15	0
2019-07-01 21:00:00	27.253864	26.963503	0.254318	0	3.532443	30	15	0
2019-07-01 21:15:00	27.152042	26.525531	0.264412	0	4.601799	30	15	0
2019-07-01 21:30:00	27.05784	26.142919	0.275232	0	5.763866	30	15	0
2019-07-01 21:45:00	26.968475	25.784729	0.285372	0	6.784443	30	15	0
2019-07-01 22:00:00	26.880169	25.440242	0.293247	0	7.464535	30	15	0
2019-07-01 22:15:00	26.796363	25.15383	0.297966	0	7.814046	30	15	0
2019-07-01 22:30:00	26.722571	24.889528	0.3015	0	7.90715	30	15	0
2019-07-01 22:45:00	26.653131	24.586397	0.306359	0	7.804959	30	15	0
2019-07-01 23:00:00	26.578328	24.17817	0.316235	0	7.452923	30	15	0
2019-07-01 23:15:00	26.488282	23.632643	0.335177	0	6.570635	30	15	0
2019-07-01 23:30:00	26.381538	23.026581	0.357379	0	5.498536	30	15	0
2019-07-01 23:45:00	26.266473	22.456411	0.374804	0	4.743954	30	15	0
2019-07-02 00:00:00	26.155494	21.989963	0.382417	0	4.717083	30	15	0
2019-07-02 00:15:00	26.053895	21.570835	0.387417	0	5.244371	30	15	0
2019-07-02 00:30:00	25.958479	21.172601	0.392417	0	5.961609	30	15	0
2019-07-02 00:45:00	25.866486	20.791688	0.397417	0	6.538641	30	15	0

End of preview. Expand in Data Studio

TTM4HVAC – Evaluation dataset (target-cool-test)

This dataset contains target-building time-series data under cooling-dominated operating conditions (July).

It is intended for evaluation / benchmarking of TTM4HVAC models on a cooling-focused scenario.

Check out the paper arXiv:XXXX.XXXXX (to be released) and visit the main repository ttm4hvac for further details.

Columns

time
Room Air Temperature (C)
Outdoor Air Temperature (C)
Outdoor Humidity (%)
Direct Solar Radiation (W/m^2)
Wind Speed (m/s)
Cooling Setpoint (C)
Heating Setpoint (C)
HVAC Power Consumption (W)

Usage

from datasets import load_dataset

ds = load_dataset("gft/ttm4hvac-target-heat-test")
df = ds["test"].to_pandas()
df.head()

✒️ 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: 21

Size of downloaded dataset files:

200 kB

Size of the auto-converted Parquet files:

200 kB

Number of rows:

2,976

Models trained or fine-tuned on gft/ttm4hvac-target-cool-test

Collection including gft/ttm4hvac-target-cool-test

ttm4hvac

Collection

10 items • Updated about 6 hours ago