Wind Turbine Power Generation Forecasting

Hourly Weather and Power Data (2013-2016)

@kaggle.sudhanvahg_wind_turbine_power_generation_forecasting

Table List

3 tables(2.96 MB)

Column Info

Test

Train

Train

@kaggle.sudhanvahg_wind_turbine_power_generation_forecasting.train

2.44 MB
140160 rows
12 columns

unnamed_0 Unnamed: 0	time Time	location Location	temp_2m Temp 2m	relhum_2m RelHum 2m	dp_2m DP 2m	ws_10m WS 10m	ws_100m WS 100m	wd_10m WD 10m	wd_100m WD 100m	wg_10m WG 10m	power Power
	02-01-2013 00:00	1	28.27960022	84.66420479	24.07259522	1.605389169	1.267799417	145.0516826	161.0573147	1.336515074	0.163495886
1	02-01-2013 01:00	1	28.17960022	85.66420479	24.27259522	2.225389169	3.997799417	150.0516826	157.0573147	4.336515074	0.142395886
2	02-01-2013 02:00	1	26.57960022	90.66420479	24.07259522	1.465389169	2.787799417	147.0516826	149.0573147	3.136515074	0.121395886
3	02-01-2013 03:00	1	27.17960022	87.66420479	23.87259522	1.465389169	2.697799417	57.05168257	104.0573147	1.536515074	0.100295886
4	02-01-2013 04:00	1	27.07960022	87.66420479	23.67259522	2.635389169	4.437799417	57.05168257	83.0573147	3.936515074	0.079295886
5	02-01-2013 05:00	1	27.37960022	89.66420479	24.77259522	2.895389169	5.597799417	65.05168257	79.0573147	4.436515074	0.077795886
6	02-01-2013 06:00	1	26.47960022	91.66420479	24.47259522	2.265389169	5.827799417	64.05168257	77.0573147	4.636515074	0.095895886
7	02-01-2013 07:00	1	28.17960022	90.66420479	25.67259522	3.265389169	6.247799417	68.05168257	77.0573147	4.736515074	0.114095886
8	02-01-2013 08:00	1	29.97960022	87.66420479	26.57259522	3.705389169	6.897799417	73.05168257	80.0573147	5.736515074	0.132195886
9	02-01-2013 09:00	1	33.77960022	81.66420479	28.67259522	3.605389169	6.017799417	81.05168257	85.0573147	6.436515074	0.150295886


CREATE TABLE train (
  "unnamed_0" BIGINT,
  "time" VARCHAR,
  "location" BIGINT,
  "temp_2m" DOUBLE,
  "relhum_2m" DOUBLE,
  "dp_2m" DOUBLE,
  "ws_10m" DOUBLE,
  "ws_100m" DOUBLE,
  "wd_10m" DOUBLE,
  "wd_100m" DOUBLE,
  "wg_10m" DOUBLE,
  "power" DOUBLE
);