Hugging Face's logo

Datasets:
Premchan369
/
quantum-ai-smart-grid-india-datasets

Languages:
English
Tags:
smart-grid
india
energy
ev-charging
solar
time-series
License:
Dataset card Data Studio Files
xet
 Community
Dataset Preview
Duplicate
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 10 new columns ({'solar_kw', 'month', 'hour', 'cloud_pct', 'dow', 'datetime', 'demand_gw', 'temp_c', 'humidity', 'wind_ms'}) and 13 missing columns ({'ev_id', 'departure_h', 'ev_model', 'target_soc', 'city', 'charger_kw', 'energy_kwh', 'date', 'arrival_h', 'initial_soc', 'state', 'battery_kwh', 'charger_type'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets/indian_grid.csv (at revision 4d0a7b213fea26e941699381d036f69c9367b860), [/tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/ev_charging_india.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/ev_charging_india.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/ev_sessions_india.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/ev_sessions_india.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/indian_grid.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/indian_grid.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/indian_power_consumption.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/indian_power_consumption.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/optimization_results.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/optimization_results.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/solar_generation_india.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/solar_generation_india.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/weather_india.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/weather_india.csv)]

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1890, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 760, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              datetime: string
              demand_gw: double
              solar_kw: double
              temp_c: double
              humidity: double
              wind_ms: double
              cloud_pct: double
              hour: int64
              month: int64
              dow: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1393
              to
              {'date': Value('string'), 'ev_id': Value('string'), 'ev_model': Value('string'), 'state': Value('string'), 'city': Value('string'), 'charger_type': Value('string'), 'charger_kw': Value('float64'), 'battery_kwh': Value('int64'), 'initial_soc': Value('float64'), 'target_soc': Value('float64'), 'energy_kwh': Value('float64'), 'arrival_h': Value('int64'), 'departure_h': Value('int64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1892, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 10 new columns ({'solar_kw', 'month', 'hour', 'cloud_pct', 'dow', 'datetime', 'demand_gw', 'temp_c', 'humidity', 'wind_ms'}) and 13 missing columns ({'ev_id', 'departure_h', 'ev_model', 'target_soc', 'city', 'charger_kw', 'energy_kwh', 'date', 'arrival_h', 'initial_soc', 'state', 'battery_kwh', 'charger_type'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets/indian_grid.csv (at revision 4d0a7b213fea26e941699381d036f69c9367b860), [/tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/ev_charging_india.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/ev_charging_india.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/ev_sessions_india.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/ev_sessions_india.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/indian_grid.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/indian_grid.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/indian_power_consumption.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/indian_power_consumption.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/optimization_results.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/optimization_results.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/solar_generation_india.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/solar_generation_india.csv), /tmp/hf-datasets-cache/medium/datasets/33745965678338-config-parquet-and-info-Premchan369-quantum-ai-sm-a0b37add/hub/datasets--Premchan369--quantum-ai-smart-grid-india-datasets/snapshots/4d0a7b213fea26e941699381d036f69c9367b860/weather_india.csv (origin=hf://datasets/Premchan369/quantum-ai-smart-grid-india-datasets@4d0a7b213fea26e941699381d036f69c9367b860/weather_india.csv)]
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

date
string
ev_id
string
ev_model
string
state
string
city
string
charger_type
string
charger_kw
float64
battery_kwh
int64
initial_soc
float64
target_soc
float64
energy_kwh
float64
arrival_h
int64
departure_h
int64
2024-01-01
EV_001
Hyundai Kona
Tamil Nadu
Chennai
AC_7.4kW
7.4
40
0.259
0.961
28.08
9
14
2024-01-01
EV_002
Tata Nexon
Karnataka
Bangalore
AC_7.4kW
7.4
75
0.518
0.951
32.475
9
15
2024-01-01
EV_003
Hyundai Kona
Gujarat
Ahmedabad
AC_7.4kW
7.4
75
0.494
0.905
30.825
10
16
2024-01-01
EV_004
Ather 450
Delhi
Delhi
AC_7.4kW
7.4
60
0.46
0.918
27.48
7
12
2024-01-01
EV_005
Hyundai Kona
Telangana
Hyderabad
AC_7.4kW
7.4
82
0.441
0.984
44.526
9
17
2024-01-01
EV_006
Hyundai Kona
Tamil Nadu
Chennai
AC_7.4kW
7.4
82
0.322
0.843
42.722
14
21
2024-01-01
EV_007
Hyundai Kona
Maharashtra
Mumbai
AC_7.4kW
7.4
25
0.254
0.925
16.775
7
11
2024-01-01
EV_008
Tata Nexon
Delhi
Delhi
AC_7.4kW
7.4
75
0.238
0.995
56.775
10
19
2024-01-01
EV_009
MG ZS
Tamil Nadu
Chennai
AC_7.4kW
7.4
60
0.446
0.857
24.66
10
15
2024-01-01
EV_010
Ola S1
Delhi
Delhi
AC_7.4kW
7.4
60
0.483
0.871
23.28
7
12
2024-01-01
EV_011
Ola S1
Maharashtra
Pune
AC_7.4kW
7.4
82
0.544
0.971
35.014
10
16
2024-01-01
EV_012
MG ZS
Maharashtra
Mumbai
DC_50kW
50
60
0.294
0.865
34.26
8
10
2024-01-01
EV_013
Tata Nexon
Gujarat
Ahmedabad
AC_7.4kW
7.4
60
0.229
0.988
45.54
9
17
2024-01-01
EV_014
Hyundai Kona
Maharashtra
Pune
DC_50kW
50
60
0.366
0.98
36.84
8
10
2024-01-01
EV_015
Hyundai Kona
Delhi
Delhi
AC_3.3kW
3.3
30
0.302
0.801
14.97
9
15
2024-01-01
EV_016
Ola S1
Tamil Nadu
Chennai
AC_7.4kW
7.4
82
0.227
0.89
54.366
9
18
2024-01-01
EV_017
Ather 450
Telangana
Hyderabad
AC_7.4kW
7.4
25
0.372
0.86
12.2
8
11
2024-01-01
EV_018
Ather 450
Telangana
Hyderabad
DC_150kW
150
40
0.512
0.849
13.48
8
10
2024-01-01
EV_019
Ola S1
Gujarat
Ahmedabad
AC_3.3kW
3.3
75
0.167
0.854
51.525
8
23
2024-01-01
EV_020
Hyundai Kona
Maharashtra
Pune
DC_50kW
50
60
0.299
0.885
35.16
8
10
2024-01-02
EV_001
Hyundai Kona
Gujarat
Ahmedabad
AC_7.4kW
7.4
60
0.198
0.853
39.3
8
15
2024-01-02
EV_002
MG ZS
Maharashtra
Pune
AC_7.4kW
7.4
75
0.263
0.861
44.85
6
14
2024-01-02
EV_003
Tata Nexon
Gujarat
Ahmedabad
AC_7.4kW
7.4
40
0.431
0.961
21.2
7
11
2024-01-02
EV_004
MG ZS
Tamil Nadu
Chennai
AC_7.4kW
7.4
75
0.284
0.945
49.575
6
14
2024-01-02
EV_005
Hyundai Kona
Delhi
Delhi
AC_7.4kW
7.4
60
0.236
0.805
34.14
10
16
2024-01-02
EV_006
Ather 450
Delhi
Delhi
AC_3.3kW
3.3
40
0.539
0.885
13.84
9
15
2024-01-02
EV_007
MG ZS
Maharashtra
Mumbai
AC_7.4kW
7.4
30
0.32
0.876
16.68
9
13
2024-01-02
EV_008
MG ZS
Maharashtra
Mumbai
DC_50kW
50
82
0.232
0.88
53.136
8
11
2024-01-02
EV_009
Tata Nexon
Gujarat
Ahmedabad
AC_7.4kW
7.4
75
0.241
0.839
44.85
7
15
2024-01-02
EV_010
Ather 450
Tamil Nadu
Chennai
AC_7.4kW
7.4
60
0.203
0.978
46.5
8
16
2024-01-02
EV_011
Ola S1
Maharashtra
Mumbai
DC_50kW
50
82
0.42
0.987
46.494
7
9
2024-01-02
EV_012
Ather 450
Delhi
Delhi
AC_3.3kW
3.3
40
0.46
0.962
20.08
6
14
2024-01-02
EV_013
Hyundai Kona
Maharashtra
Mumbai
AC_7.4kW
7.4
60
0.425
0.912
29.22
8
13
2024-01-02
EV_014
Hyundai Kona
Telangana
Hyderabad
AC_7.4kW
7.4
82
0.483
0.942
37.638
8
15
2024-01-02
EV_015
MG ZS
Delhi
Delhi
DC_50kW
50
82
0.466
0.836
30.34
9
11
2024-01-02
EV_016
MG ZS
Karnataka
Bangalore
AC_7.4kW
7.4
75
0.285
0.845
42
7
14
2024-01-02
EV_017
Hyundai Kona
Karnataka
Bangalore
DC_50kW
50
82
0.296
0.88
47.888
6
8
2024-01-02
EV_018
Ather 450
Delhi
Delhi
AC_7.4kW
7.4
40
0.301
0.899
23.92
8
13
2024-01-02
EV_019
Ather 450
Maharashtra
Pune
DC_50kW
50
82
0.184
0.943
62.238
6
9
2024-01-02
EV_020
Ola S1
Telangana
Hyderabad
AC_7.4kW
7.4
40
0.505
0.83
13
10
13
2024-01-03
EV_001
Hyundai Kona
Telangana
Hyderabad
AC_7.4kW
7.4
40
0.522
0.943
16.84
9
13
2024-01-03
EV_002
MG ZS
Telangana
Hyderabad
DC_50kW
50
82
0.546
0.99
36.408
8
10
2024-01-03
EV_003
MG ZS
Maharashtra
Pune
AC_7.4kW
7.4
82
0.384
0.924
44.28
8
15
2024-01-03
EV_004
Ather 450
Karnataka
Bangalore
AC_7.4kW
7.4
30
0.528
0.82
8.76
11
14
2024-01-03
EV_005
Hyundai Kona
Karnataka
Bangalore
AC_7.4kW
7.4
75
0.247
0.979
54.9
8
17
2024-01-03
EV_006
Ather 450
Karnataka
Bangalore
AC_7.4kW
7.4
60
0.42
0.86
26.4
9
14
2024-01-03
EV_007
Tata Nexon
Maharashtra
Pune
DC_50kW
50
82
0.351
0.98
51.578
7
10
2024-01-03
EV_008
MG ZS
Karnataka
Bangalore
AC_7.4kW
7.4
30
0.29
0.867
17.31
11
15
2024-01-03
EV_009
Ola S1
Telangana
Hyderabad
DC_50kW
50
75
0.375
0.968
44.475
9
11
2024-01-03
EV_010
Hyundai Kona
Maharashtra
Mumbai
AC_7.4kW
7.4
75
0.365
0.963
44.85
10
18
2024-01-03
EV_011
Ather 450
Gujarat
Ahmedabad
AC_7.4kW
7.4
75
0.493
0.855
27.15
6
11
2024-01-03
EV_012
Ola S1
Maharashtra
Pune
DC_50kW
50
60
0.387
0.9
30.78
7
9
2024-01-03
EV_013
Hyundai Kona
Maharashtra
Mumbai
AC_7.4kW
7.4
82
0.471
0.802
27.142
9
14
2024-01-03
EV_014
Ola S1
Delhi
Delhi
AC_7.4kW
7.4
40
0.436
0.928
19.68
10
14
2024-01-03
EV_015
Ola S1
Delhi
Delhi
AC_7.4kW
7.4
82
0.399
0.844
36.49
10
16
2024-01-03
EV_016
Ather 450
Delhi
Delhi
AC_7.4kW
7.4
75
0.211
0.921
53.25
8
17
2024-01-03
EV_017
Tata Nexon
Karnataka
Bangalore
AC_7.4kW
7.4
60
0.183
0.945
45.72
7
15
2024-01-03
EV_018
Hyundai Kona
Delhi
Delhi
DC_50kW
50
30
0.478
0.835
10.71
7
9
2024-01-03
EV_019
Ather 450
Maharashtra
Pune
AC_7.4kW
7.4
40
0.248
0.808
22.4
11
16
2024-01-03
EV_020
Ola S1
Maharashtra
Pune
AC_7.4kW
7.4
82
0.364
0.87
41.492
9
16
2024-01-04
EV_001
Ather 450
Maharashtra
Mumbai
DC_150kW
150
60
0.237
0.904
40.02
10
12
2024-01-04
EV_002
MG ZS
Tamil Nadu
Chennai
AC_3.3kW
3.3
25
0.257
0.976
17.975
11
18
2024-01-04
EV_003
Ather 450
Maharashtra
Mumbai
AC_3.3kW
3.3
75
0.164
0.968
60.3
6
23
2024-01-04
EV_004
Hyundai Kona
Maharashtra
Mumbai
AC_7.4kW
7.4
25
0.341
0.989
16.2
7
11
2024-01-04
EV_005
MG ZS
Maharashtra
Mumbai
AC_7.4kW
7.4
25
0.412
0.993
14.525
7
10
2024-01-04
EV_006
MG ZS
Delhi
Delhi
AC_7.4kW
7.4
60
0.484
0.821
20.22
6
10
2024-01-04
EV_007
Tata Nexon
Delhi
Delhi
DC_50kW
50
25
0.548
0.836
7.2
9
11
2024-01-04
EV_008
MG ZS
Delhi
Delhi
AC_7.4kW
7.4
40
0.409
0.813
16.16
7
11
2024-01-04
EV_009
Ather 450
Telangana
Hyderabad
AC_7.4kW
7.4
40
0.305
0.982
27.08
7
12
2024-01-04
EV_010
Tata Nexon
Delhi
Delhi
AC_3.3kW
3.3
40
0.365
0.982
24.68
8
17
2024-01-04
EV_011
Hyundai Kona
Tamil Nadu
Chennai
AC_7.4kW
7.4
25
0.423
0.803
9.5
8
11
2024-01-04
EV_012
Ola S1
Karnataka
Bangalore
AC_7.4kW
7.4
82
0.228
0.962
60.188
11
21
2024-01-04
EV_013
Ola S1
Delhi
Delhi
AC_7.4kW
7.4
25
0.407
0.859
11.3
9
12
2024-01-04
EV_014
Ola S1
Gujarat
Ahmedabad
AC_7.4kW
7.4
30
0.359
0.82
13.83
6
9
2024-01-04
EV_015
Hyundai Kona
Tamil Nadu
Chennai
AC_7.4kW
7.4
75
0.326
0.98
49.05
7
15
2024-01-04
EV_016
Tata Nexon
Maharashtra
Mumbai
AC_7.4kW
7.4
60
0.428
0.849
25.26
7
12
2024-01-04
EV_017
Tata Nexon
Delhi
Delhi
AC_7.4kW
7.4
40
0.527
0.898
14.84
11
15
2024-01-04
EV_018
MG ZS
Delhi
Delhi
AC_7.4kW
7.4
60
0.44
0.857
25.02
11
16
2024-01-04
EV_019
Ather 450
Karnataka
Bangalore
AC_7.4kW
7.4
60
0.152
0.934
46.92
8
16
2024-01-04
EV_020
Ather 450
Karnataka
Bangalore
AC_7.4kW
7.4
30
0.464
0.998
16.02
7
11
2024-01-05
EV_001
Hyundai Kona
Maharashtra
Pune
DC_50kW
50
40
0.206
0.822
24.64
9
11
2024-01-05
EV_002
Ola S1
Tamil Nadu
Chennai
AC_7.4kW
7.4
60
0.316
0.805
29.34
9
14
2024-01-05
EV_003
Ola S1
Telangana
Hyderabad
AC_3.3kW
3.3
30
0.538
0.806
8.04
8
12
2024-01-05
EV_004
Ather 450
Delhi
Delhi
AC_7.4kW
7.4
82
0.161
0.841
55.76
6
15
2024-01-05
EV_005
Hyundai Kona
Maharashtra
Mumbai
DC_50kW
50
30
0.382
0.914
15.96
8
10
2024-01-05
EV_006
Hyundai Kona
Tamil Nadu
Chennai
AC_7.4kW
7.4
30
0.266
0.871
18.15
8
12
2024-01-05
EV_007
Ola S1
Gujarat
Ahmedabad
AC_7.4kW
7.4
40
0.545
0.807
10.48
7
10
2024-01-05
EV_008
MG ZS
Karnataka
Bangalore
AC_7.4kW
7.4
30
0.254
0.949
20.85
6
10
2024-01-05
EV_009
MG ZS
Karnataka
Bangalore
AC_3.3kW
3.3
30
0.473
0.857
11.52
10
15
2024-01-05
EV_010
MG ZS
Gujarat
Ahmedabad
AC_7.4kW
7.4
30
0.363
0.999
19.08
8
12
2024-01-05
EV_011
Ather 450
Gujarat
Ahmedabad
AC_3.3kW
3.3
30
0.407
0.92
15.39
7
13
2024-01-05
EV_012
MG ZS
Maharashtra
Mumbai
DC_50kW
50
60
0.299
0.971
40.32
6
8
2024-01-05
EV_013
Ola S1
Maharashtra
Mumbai
DC_150kW
150
82
0.195
0.996
65.682
7
9
2024-01-05
EV_014
Ather 450
Gujarat
Ahmedabad
AC_7.4kW
7.4
40
0.388
0.967
23.16
9
14
2024-01-05
EV_015
Ola S1
Tamil Nadu
Chennai
AC_7.4kW
7.4
40
0.201
0.895
27.76
10
15
2024-01-05
EV_016
Ola S1
Maharashtra
Pune
AC_7.4kW
7.4
75
0.424
0.904
36
10
16
2024-01-05
EV_017
Hyundai Kona
Delhi
Delhi
AC_7.4kW
7.4
60
0.258
0.988
43.8
7
14
2024-01-05
EV_018
MG ZS
Delhi
Delhi
AC_7.4kW
7.4
82
0.207
0.948
60.762
12
22
2024-01-05
EV_019
Ather 450
Karnataka
Bangalore
AC_7.4kW
7.4
60
0.244
0.883
38.34
12
19
2024-01-05
EV_020
Ola S1
Tamil Nadu
Chennai
DC_50kW
50
75
0.272
0.827
41.625
6
8
End of preview.

Indian Smart Grid Datasets (Full Year Simulation)

File Rows Description
indian_power_consumption.csv 8,760 Hourly demand + weather
solar_generation_india.csv 17,520 2-plant solar generation
ev_charging_india.csv 7,300 EV sessions (20 EVs × 365 days)
weather_india.csv 8,760 Hourly weather
Downloads last month
15
Total file size:
2.84 MB