Energy
16 columns
200 rows
8 formats

Renewable Power Generation Metrics

This dataset provides synthetic, hourly renewable power generation metrics from solar and wind sites worldwide, including site details, generation output, capacity, environmental conditions, and data quality indicators. It is ideal for energy forecasting, grid modeling, and sustainability benchmarking, supporting advanced analytics and operational decision-making for renewable energy stakeholders.

last updated 21 Aug 2025
by GoMask

The brief that made it

Short-term and long-term energy forecasting for grid operators

Sample rows

preview · 8 of 200 rows · all 16 columns

site_idstring	site_typestring	temperature_cfloat	countrystring	site_namestring	latitudefloat	longitudefloat	regionstring	datetime_utcdatetime	power_generated_mwfloat	capacity_mwfloat	availability_factorfloat	performance_ratiofloat	wind_speed_mpsfloat	solar_irradiance_wm2float	data_quality_flagboolean
SOLAR_USA_001	solar	41.3	USA	Desert Sun Valley	33.45	-115.85	California	2024-06-01T18:00:00Z	180.2	200	0.97	0.92	blank	1100.4	true
WIND_CHINA_002	wind	19.6	China	Coastal Wind Array	37.88	121.56	Shandong	2024-04-21T03:00:00Z	320.7	400	0.95	0.9	23.2	blank	true
SOLAR_INDIA_003	solar	44.5	India	Rajasthan Solar Park	27.02	73.01	Rajasthan	2024-05-15T11:00:00Z	125.1	140	0.99	0.9	blank	1207.6	true
WIND_GERMANY_004	wind	8.3	Germany	Baltic Breeze Farm	54.56	13.22	Mecklenburg	2024-03-12T16:00:00Z	72	80	0.93	0.89	17.6	blank	true
SOLAR_EGYPT_005	solar	45	Egypt	Nile Delta Array	30.58	31.23	Gharbia	2024-07-06T13:00:00Z	75.5	80	0.96	0.88	blank	1056.9	true
WIND_BRAZIL_006	wind	29.2	Brazil	Atlantic Gust Plains	-5.04	-35.13	Rio Grande do Norte	2024-09-10T18:00:00Z	345.1	400	0.98	0.94	31.4	blank	true
SOLAR_FRANCE_007	solar	36.7	France	Provence Solar Estate	43.68	6.93	Provence-Alpes	2024-06-15T10:00:00Z	47.8	50	0.99	0.91	blank	1012.3	true
WIND_ICELAND_008	wind	-14.6	Iceland	North Fjord Winds	65.95	-19.53	Nordurland	2024-01-30T05:00:00Z	9.2	10	0.92	0.93	13.1	blank	true
SOLAR_MEXICO_009	solar	38.9	Mexico	Sonora Light Fields	29.09	-110.54	Sonora	2024-05-05T15:00:00Z	115.6	120	0.97	0.9	blank	1201.7	true
WIND_SAFRICA_010	wind	21.5	South Africa	Cape Gale Ridge	-33.89	18.42	Western Cape	2024-08-12T09:00:00Z	76.2	80	0.96	0.91	21.7	blank	true
SOLAR_SPAIN_011	solar	40.1	Spain	Andalusia Bright Fields	37.39	-4.84	Andalusia	2024-06-28T14:00:00Z	48.5	50	0.98	0.93	blank	1111.6	true
WIND_UK_012	wind	6.9	UK	North Sea Windworks	53.4	1.06	Yorkshire	2024-03-29T22:00:00Z	19.8	25	0.82	0.67	12.4	blank	true
SOLAR_INDIA_013	solar	37.4	India	Gujarat Sun Arrays	22.92	72.65	Gujarat	2024-04-08T08:00:00Z	89.3	100	0.95	0.89	blank	1016.8	true
WIND_FRANCE_014	wind	14.2	France	Normandy Turbine Farm	49.19	-0.37	Normandy	2024-05-17T17:00:00Z	22.7	25	0.9	0.83	11.2	blank	true
SOLAR_ARCTIC_015	solar	-85.2	Arctic	Polar Ice Array	90	180	blank	2024-12-01T03:00:00Z	0	1	0.1	0	blank	0	true
WIND_ANTARCTICA_016	wind	-81.6	Antarctica	Southern Ice Turbine	-90	-180	blank	2024-07-25T16:00:00Z	0	1	0.05	0	0	blank	true
SOLAR_FRANCE_017	solar	41.2	France	Languedoc Sunfields	43.65	3.87	Languedoc	2024-06-15T12:00:00Z	99.7	100	1	0.99	blank	1226.7	true
WIND_GERMANY_018	wind	2.5	Germany	Black Forest Wind	48.25	8.21	Baden-Württemberg	2024-02-11T19:00:00Z	10.8	25	0.43	0.44	9.5	blank	true
SOLAR_MEXICO_019	solar	42	Mexico	Baja Solar Flats	27.65	-113.16	Baja California	2024-05-24T17:00:00Z	79.1	80	0.98	0.9	blank	1188.3	true
WIND_BRAZIL_020	wind	19.3	Brazil	Pampas Wind Complex	-32.03	-53.36	Rio Grande do Sul	2024-11-02T10:00:00Z	23.9	25	0.95	0.83	13.3	blank	true

What the 200 rows show

from the 200-row sample

Solar (site type) stands out: mean temperature_c is 33.7, against 9.3 for the rest.

25.0median temperature_c
72.2median power_generated_mw
80median capacity_mw
0.92median availability_factor
0.89median performance_ratio
13.1median wind_speed_mps

Mean temperature_c by site_type200 rows

temperature_c200 rows, in bands of 20

Median 25.0, from -85.2 to 49.2.

country200 rows · top 10 of 14 values

France24
India22
China20
Germany20
Brazil18
Mexico18
South Africa17
Egypt16
USA14
Iceland13

16 columns by typefrom the column list below

string 5
float 9
datetime 1
boolean 1

Columns

16 columns in four groups

blueprint · 16 columns
column	type	description	example
Text 5 columns
`site_id`	string	Unique identifier for each renewable power generation site	SOLAR_USA_001
`site_name`	string	Human-readable name of the site	Desert Sun Valley
`site_type`	string	Type of renewable site (solar or wind)solar · wind	solar
`country`	string	Country where the site is located	USA
`region`	string	Region or state/province of the siteoptional	California
Numbers 9 columns
`latitude`	float	Latitude coordinate of the site-90 to 90	33.45
`longitude`	float	Longitude coordinate of the site-180 to 180	-115.85
`power_generated_mw`	float	Total power generated during the hour in megawatts0 or more	180.2
`capacity_mw`	float	Installed capacity of the site in megawatts0 or more	200
`availability_factor`	float	Fraction of time the site was available for generation during the hour (0-1)0 to 1 · optional	0.97
`performance_ratio`	float	Ratio of actual to expected generation (0-1), useful for benchmarking0 to 1 · optional	0.92
`temperature_c`	float	Ambient temperature at the site during the hour in Celsiusoptional	41.3
`wind_speed_mps`	float	Average wind speed at the site during the hour in meters per second (for wind sites)0 or more · optional	23.2
`solar_irradiance_wm2`	float	Average solar irradiance at the site during the hour in watts per square meter (for solar sites)0 or more · optional	1100.4
Dates and times 1 column
`datetime_utc`	datetime	Timestamp of the metric record in UTC	2024-06-01T18:00:00Z
True or false 1 column
`data_quality_flag`	boolean	Indicates if the data for this record passed quality checksoptional	true

Use it for

An energy dashboard
Temperature_c by site_type and a breakdown of country. Excel, Power BI or Tableau.
Why do the 99 solar rows have a mean temperature_c of 33.7?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Sites200
SOLAR_USA_00141.3solar
WIND_CHINA_00219.6wind
SOLAR_INDIA_00344.5solar
A software demo
Believable sites with site_name, site_type and latitude to fill a screen in front of a buyer.

This dataset200 rows16 columns

Yours1,000 rows16 columnssite_id: UK only

blueprint · renewable-power-generation-metrics

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

Site type: solar, wind
Power generated per hour (kWh: 0-300)
Weather impact on output simulated
Anomaly events flagged

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: renewable-power-generation-metrics

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?