Renewable Energy Output Patterns
This dataset provides granular, hourly records of energy output from diverse renewable sources, including solar, wind, hydro, and more, across multiple generation sites. It includes site location, capacity, environmental conditions, and whether the data is measured or estimated, enabling robust forecasting, operational optimization, and grid load balancing analyses.
Sample rows
preview · 8 of 144 rows · all 14 columns| record_idstring | energy_source_typestring | capacity_mwfloat | is_estimatedboolean | site_idstring | site_namestring | latitudefloat | longitudefloat | datetime_utcdatetime | energy_output_mwhfloat | temperature_cfloat | wind_speed_mpsfloat | solar_irradiance_wm2float | precipitation_mmfloat |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rec001 | solar | 95 | false | SOLA001 | Atacama Desert Solar | -24.2743 | -69.2875 | 2024-06-01T15:00:00Z | 88.2 | 36.7 | blank | 920 | 0 |
| rec002 | wind | 45 | false | WIND001 | North Sea Wind Farm | 54.321 | 3.8765 | 2024-06-01T04:00:00Z | 39.6 | 10.3 | 13.2 | blank | 1.2 |
| rec003 | hydro | 800 | false | HYDR001 | Columbia River Hydro | 46.2392 | -120.9871 | 2024-06-01T13:00:00Z | 760 | 15.7 | blank | blank | 2.5 |
| rec004 | geothermal | 34 | false | GEOT001 | Yellowstone Caldera Geo | 44.4279 | -110.5885 | 2024-06-01T10:00:00Z | 27.4 | 18.2 | blank | blank | 0 |
| rec005 | biomass | 18 | true | BIOM001 | Black Forest Biomass | 48.1222 | 8.2315 | 2024-06-01T11:00:00Z | 10 | 25.2 | blank | blank | 0 |
| rec006 | solar | 84 | false | SOLA002 | Mojave Basin Solar | 35.0113 | -117.3451 | 2024-06-01T18:00:00Z | 79.5 | 41.1 | blank | 870 | 0 |
| rec007 | wind | 40 | false | WIND002 | Cape Horn Wind | -55.9833 | -67.2667 | 2024-06-01T22:00:00Z | 32.1 | 3.7 | 16.5 | blank | 2.8 |
| rec008 | hydro | 710 | true | HYDR002 | Amazonia Hydro Plant | -3.4653 | -62.2159 | 2024-06-01T15:00:00Z | 672 | 23.9 | blank | blank | 8.6 |
| rec009 | geothermal | 22 | false | GEOT002 | Iceland Rift Geo | 64.9631 | -19.0208 | 2024-06-01T00:00:00Z | 20.5 | 5.1 | blank | blank | 2.3 |
| rec010 | biomass | 14 | true | BIOM002 | Sumatra Urban Biomass | -0.7893 | 101.2642 | 2024-06-01T16:00:00Z | 7.7 | 32.8 | blank | blank | 3.1 |
| rec011 | solar | 95 | false | SOLA003 | Kalahari Solar Field | -22.9581 | 22.9385 | 2024-06-01T10:00:00Z | 91.3 | 39.4 | blank | 970 | 0.1 |
| rec012 | wind | 32 | false | WIND003 | Falklands Wind Farm | -51.7963 | -59.5236 | 2024-06-01T12:00:00Z | 23.7 | 6.8 | 19.4 | blank | 2 |
| rec013 | hydro | 340 | true | HYDR003 | Volta Reservoir Hydro | 6.5069 | -0.5479 | 2024-06-01T17:00:00Z | 320 | 27 | blank | blank | 7.5 |
| rec014 | geothermal | 24 | true | GEOT003 | Ring of Fire Geo | -8.3405 | 115.092 | 2024-06-01T06:00:00Z | 17.8 | 29.3 | blank | blank | 0 |
| rec015 | biomass | 8 | true | BIOM003 | Alaska Rural Biomass | 64.2008 | -149.4937 | 2024-06-01T23:00:00Z | 2.9 | 12.5 | blank | blank | 0 |
| rec016 | solar | 81 | false | SOLA004 | Sonoran Solar Park | 32.2163 | -113.7633 | 2024-06-01T19:00:00Z | 74 | 38 | blank | 845 | 0 |
| rec017 | wind | 27 | false | WIND004 | Baltic Sea Wind | 56.4321 | 18.2304 | 2024-06-01T15:00:00Z | 21.3 | 17.5 | 10.1 | blank | 0.8 |
| rec018 | hydro | 420 | false | HYDR004 | St. Lawrence Hydro | 45.0081 | -74.7528 | 2024-06-01T08:00:00Z | 420 | 14.2 | blank | blank | 3.2 |
| rec019 | geothermal | 22 | false | GEOT004 | Azores Deep Geo | 37.7412 | -25.6756 | 2024-06-01T05:00:00Z | 18.5 | 21.9 | blank | blank | 1.1 |
| rec020 | biomass | 20 | true | BIOM004 | Congo Basin Biomass | -0.228 | 15.8277 | 2024-05-30T09:00:00Z | 12.6 | 28.4 | blank | blank | 7.9 |
What the 144 rows show
from the 144-row sampleHydro (energy source type) stands out: mean capacity_
- 29%is_
estimated = true - 38median capacity_
mw - 28.8median energy_
output_ mwh - 21.3median temperature_
c - 11.8median wind_
speed_ mps - 887.0median solar_
irradiance_ wm2
Median 38, from 8 to 1,200.
- string 4
- float 8
- datetime 1
- boolean 1
Columns
14 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 4 columns | |||
record_id | string | Unique identifier for each hourly energy output record.unique | rec001 |
site_id | string | Unique identifier for the renewable energy generation site. | SOLA001 |
site_name | string | Descriptive name of the renewable energy site. | Atacama Desert Solar |
energy_source_type | string | Type of renewable energy source (e.g., solar, wind, hydro, geothermal, biomass).solar · wind · hydro · geothermal · biomass | solar |
| Numbers 8 columns | |||
latitude | float | Latitude coordinate of the energy site.-90 to 90 | -24.2743 |
longitude | float | Longitude coordinate of the energy site.-180 to 180 | -69.2875 |
energy_output_mwh | float | Amount of energy produced in megawatt-hours (MWh) during the hour.0 or more | 88.2 |
capacity_mw | float | Maximum generation capacity of the site in megawatts (MW).0 or more | 95 |
temperature_c | float | Ambient temperature at the site during the hour, in degrees Celsius.optional | 36.7 |
wind_speed_mps | float | Average wind speed at the site during the hour, in meters per second. Relevant for wind sites.0 or more · optional | 13.2 |
solar_irradiance_wm2 | float | Average solar irradiance at the site during the hour, in watts per square meter. Relevant for solar sites.0 or more · optional | 920 |
precipitation_mm | float | Total precipitation at the site during the hour, in millimeters.0 or more · optional | 0 |
| Dates and times 1 column | |||
datetime_utc | datetime | Timestamp in UTC for the start of the hourly measurement period. | 2024-06-01T15:00:00Z |
| True or false 1 column | |||
is_estimated | boolean | Indicates if the energy output value is estimated (true) or measured (false). | false |
Use it for
An energy dashboard
The is_
estimated rate and capacity_ mw by energy_ source_ type. Excel, Power BI or Tableau. Why do the 29 hydro rows have a mean capacity_
mw of 514.6? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Records144rec00195solarrec00518biomassrec008710hydro
A software demo
Believable records with site_
id, site_ name and latitude to fill a screen in front of a buyer.
This dataset144 rows14 columns
Yours1,000 rows14 columnssite_id: UK only
blueprint · renewable-energy-output-patterns
Behind this dataset
Same schema. As many rows as you need.
These 144 rows came out of a blueprint — 14 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
- Record output per source type
- Log hourly production values
- Flag output fluctuations over 10%
- Summarize daily and monthly trends
- Differentiate between solar and wind
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-energy-output-patterns