Energy
16 columns
200 rows
8 formats

Energy Wind Farm Output Logs

This dataset provides detailed, time-stamped output logs from wind farms, including measured and forecasted power generation, weather conditions, and operational status. It enables robust analysis for clean energy forecasting, trading strategies, and grid integration optimization, supporting both research and industry applications.

last updated 20 Aug 2025
by GoMask

The brief that made it

Renewable energy output forecasting and modeling

Sample rows

preview · 8 of 200 rows · all 16 columns

log_idstring	statusstring	wind_speed_mpsfloat	farm_location_statestring	farm_idstring	farm_namestring	farm_location_latitudefloat	farm_location_longitudefloat	farm_location_countrystring	farm_location_citystring	timestampdatetime	output_power_mwfloat	turbine_countinteger	temperature_celsiusfloat	precipitation_mmfloat	forecasted_output_mwfloat
log-0001-A	operational	13.2	Rhode Island	WF-001	North Ridge Wind	41.8236	-71.4222	USA	Providence	2024-04-01T08:15:00Z	124	35	23.7	1.2	127.5
log-0002-B	operational	12.1	Rhode Island	WF-001	North Ridge Wind	41.8236	-71.4222	USA	Providence	2024-04-01T14:45:00Z	118.4	35	19.2	0.3	120
log-0003-C	operational	8.9	Arizona	WF-002	Desert Breeze	33.4484	-112.074	USA	Phoenix	2024-04-02T11:20:00Z	90.2	28	38	0	91.5
log-0004-D	operational	7.1	Arizona	WF-002	Desert Breeze	33.4484	-112.074	USA	Phoenix	2024-04-02T17:35:00Z	85	28	41.2	0	87.8
log-0005-E	operational	10.5	Texas	WF-003	Green Plains	31.9686	-99.9018	USA	Abilene	2024-04-03T09:00:00Z	98.2	42	28.9	1.2	100
log-0006-F	partial	8.1	Texas	WF-003	Green Plains	31.9686	-99.9018	USA	Abilene	2024-04-03T15:30:00Z	63.3	42	27.8	0.5	70.2
log-0007-G	operational	9.3	England	WF-004	Oceanic Haven	51.5074	-0.1278	UK	London	2024-04-04T10:10:00Z	55.6	12	13.2	10	58
log-0008-H	maintenance	5.1	England	WF-004	Oceanic Haven	51.5074	-0.1278	UK	London	2024-04-04T18:45:00Z	34.2	12	11	14.1	36
log-0009-I	operational	9.3	Vilnius	WF-005	Baltic Wind	54.6872	25.2797	Lithuania	Vilnius	2024-04-05T06:30:00Z	18.7	6	1	23.4	20.7
log-0010-J	partial	5.1	Vilnius	WF-005	Baltic Wind	54.6872	25.2797	Lithuania	Vilnius	2024-04-05T17:00:00Z	10.8	6	1	49.8	11.7
log-0011-K	operational	12.1	Bern	WF-006	Alpine Winds	46.948	7.4474	Switzerland	Bern	2024-04-06T08:30:00Z	28.7	9	8.3	14.1	30
log-0012-L	partial	2.4	Bern	WF-006	Alpine Winds	46.948	7.4474	Switzerland	Bern	2024-04-06T16:15:00Z	5.7	9	5.5	23.4	7.1
log-0013-M	offline	0	blank	WF-007	Polar Array	-82.8628	135	Antarctica	blank	2024-04-07T07:00:00Z	0	4	-89.2	0	0
log-0014-N	offline	0	blank	WF-007	Polar Array	-82.8628	135	Antarctica	blank	2024-04-07T18:00:00Z	0	4	-49	0	0
log-0015-O	operational	3.5	Red Sea	WF-008	Sahara Edge	27.9878	34.3759	Egypt	Hurghada	2024-04-08T09:45:00Z	2.5	2	49.9	0	2.8
log-0016-P	offline	0	Red Sea	WF-008	Sahara Edge	27.9878	34.3759	Egypt	Hurghada	2024-04-08T16:20:00Z	0	2	38	0	0
log-0017-Q	operational	11.7	Mendoza	WF-009	Andes Crest	-32.8908	-68.8272	Argentina	Mendoza	2024-04-09T08:40:00Z	10.8	8	17.5	49.8	12.1
log-0018-R	partial	8.9	Mendoza	WF-009	Andes Crest	-32.8908	-68.8272	Argentina	Mendoza	2024-04-09T15:10:00Z	5.7	8	16.8	14.1	7.1
log-0019-S	operational	3.2	Svalbard	WF-010	Coastal Shelter	78.2232	15.6469	Norway	blank	2024-04-10T12:00:00Z	1	3	-20.5	0.6	1.2
log-0020-T	offline	0	Svalbard	WF-010	Coastal Shelter	78.2232	15.6469	Norway	blank	2024-04-10T18:10:00Z	0	3	-28.4	0	0

What the 200 rows show

from the 200-row sample

Offline status stands out: mean wind_speed_mps is 0.0, against 9.7 for the rest.

9.1median wind_speed_mps
15farm location countries
37farm location cities
21.6median output_power_mw
11median turbine_count
13.2median temperature_celsius

Mean wind_speed_mps by status200 rows

wind_speed_mps200 rows, in bands of 2.5

Median 9.1, from 0.0 to 21.6.

farm_location_state192 rows with a value · 8 left blank

Tokyo15
Zurich15
Mendoza14
Ontario14
California12
Bern11
Rhode Island10
England10
Texas9
Vilnius9

16 columns by typefrom the column list below

string 7
integer 1
float 7
datetime 1

Columns

16 columns in three groups

blueprint · 16 columns
column	type	description	example
Text 7 columns
`log_id`	string	Unique identifier for each wind farm output log entryunique	log-0001-A
`farm_id`	string	Unique identifier for the wind farm	WF-001
`farm_name`	string	Name of the wind farm	North Ridge Wind
`farm_location_country`	string	Country where the wind farm is located	USA
`farm_location_state`	string	State or region where the wind farm is locatedoptional	Rhode Island
`farm_location_city`	string	City or locality of the wind farmoptional	Providence
`status`	string	Operational status of the wind farm at the time of loggingoperational · maintenance · offline · partial · optional	operational
Numbers 8 columns
`farm_location_latitude`	float	Latitude coordinate of the wind farm location-90 to 90	41.8236
`farm_location_longitude`	float	Longitude coordinate of the wind farm location-180 to 180	-71.4222
`output_power_mw`	float	Measured output power from the wind farm in megawatts (MW)0 or more	124
`wind_speed_mps`	float	Average wind speed at the time of logging, measured in meters per second (m/s)0 or more · optional	13.2
`turbine_count`	integer	Number of turbines in the wind farm1 or more · optional	35
`temperature_celsius`	float	Ambient temperature at the wind farm during the log, in degrees Celsiusoptional	23.7
`precipitation_mm`	float	Precipitation level at the wind farm during the log, in millimeters0 or more · optional	1.2
`forecasted_output_mw`	float	Forecasted output power for the wind farm at the time of logging, in megawatts (MW)0 or more · optional	127.5
Dates and times 1 column
`timestamp`	datetime	Date and time when the output log was recorded	2024-04-01T08:15:00Z

Use it for

An energy dashboard
Wind_speed_mps by status and a breakdown of farm_location_state. Excel, Power BI or Tableau.
Why do the 29 offline rows have a mean wind_speed_mps of 0.0?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Logs200
log-0001-A13.2operatio…
log-0002-B12.1operatio…
log-0003-C8.9operatio…
A software demo
Believable logs with farm_id, farm_name and farm_location_latitude to fill a screen in front of a buyer.

This dataset200 rows16 columns

Yours1,000 rows16 columnsfarm_location_latitude: UK only

blueprint · energy-wind-farm-output-logs

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 16 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Include farm ID and turbine count
Track hourly output per turbine
Segment by wind speed band
Flag low-output intervals

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: energy-wind-farm-output-logs

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

An energy dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Energy

What should your data show?