Energy Solar Output Time Series
This dataset provides detailed synthetic time series readings of solar panel output, including power generation, environmental conditions, and site metadata. It enables robust modeling of renewable energy production, supports forecasting, and allows for analysis of the impact of weather and site characteristics on solar performance. Ideal for researchers, energy analysts, and clean tech developers.
Sample rows
preview · 8 of 200 rows · all 13 columns| reading_idstring | weather_conditionstring | site_elevation_mfloat | panel_idstring | site_idstring | timestampdatetime | output_power_kwfloat | ambient_temperature_cfloat | irradiance_w_m2float | panel_orientation_degfloat | panel_tilt_degfloat | site_latitudefloat | site_longitudefloat |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| RDG-00001 | clear | 10 | PNL-A1001 | SITE-URBAN-01 | 2024-06-01T08:15:00Z | 4.85 | 22.5 | 990 | 180 | 25 | 40.7128 | -74.006 |
| RDG-00002 | snow | 2200 | PNL-B1102 | SITE-MOUNTAIN-02 | 2024-06-01T09:20:00Z | 2.2 | 1.3 | 720 | 45 | 40 | 46.8523 | -121.7603 |
| RDG-00003 | rain | -35 | PNL-C1203 | SITE-VALLEY-01 | 2024-06-01T10:00:00Z | 0 | -6.4 | 0 | 200 | 18 | 36.7783 | -119.4179 |
| RDG-00004 | clear | 350 | PNL-D1304 | SITE-DESERT-01 | 2024-06-01T13:40:00Z | 7.1 | 44.7 | 1620 | 180 | 14 | 33.4484 | -112.074 |
| RDG-00005 | fog | 7 | PNL-E1405 | SITE-OCEAN-01 | 2024-06-01T07:50:00Z | 0 | 14.2 | 0 | 85 | 22 | 47.6062 | -122.3321 |
| RDG-00006 | cloudy | 3 | PNL-F1506 | SITE-ISLAND-01 | 2024-06-01T11:10:00Z | 3.66 | 19.8 | 1010 | 80 | 26 | 21.3069 | -157.8583 |
| RDG-00007 | clear | 70 | PNL-G1607 | SITE-RURAL-01 | 2024-06-01T14:30:00Z | 5.3 | 28.4 | 1100 | 135 | 30 | 41.8781 | -87.6298 |
| RDG-00008 | clear | 15 | PNL-H1708 | SITE-COASTAL-01 | 2024-06-01T12:45:00Z | 4.18 | 23 | 840 | 220 | 20 | 34.0195 | -118.4912 |
| RDG-00009 | snow | 1600 | PNL-I1809 | SITE-HIGHLAND-01 | 2024-06-01T09:45:00Z | 2.4 | 7.1 | 700 | 45 | 35 | 55.3781 | -3.436 |
| RDG-00010 | partly-cloudy | 20 | PNL-J1910 | SITE-URBAN-02 | 2024-06-01T09:35:00Z | 4.22 | 19.4 | 870 | 90 | 18 | 34.0522 | -118.2437 |
| RDG-00011 | fog | 2100 | PNL-K2011 | SITE-MOUNTAIN-03 | 2024-06-01T08:10:00Z | 1.9 | -9.2 | 670 | 0 | 50 | 44.428 | -110.5885 |
| RDG-00012 | cloudy | -355 | PNL-L2112 | SITE-DEEPVALLEY-01 | 2024-06-01T07:00:00Z | 0 | -13.7 | 0 | 300 | 80 | 35.1983 | -111.6513 |
| RDG-00013 | partly-cloudy | 60 | PNL-M2213 | SITE-REMOTE-01 | 2024-06-01T14:00:00Z | 5.52 | 25.7 | 1050 | 270 | 28 | 51.5074 | -0.1278 |
| RDG-00014 | cloudy | 10 | PNL-N2314 | SITE-VALLEY-02 | 2024-06-01T13:15:00Z | 2.85 | 11.2 | 710 | 30 | 22 | 37.7749 | -122.4194 |
| RDG-00015 | clear | 6 | PNL-O2415 | SITE-ISLAND-02 | 2024-06-01T15:05:00Z | 5 | 29.1 | 1000 | 80 | 28 | 18.4655 | -66.1057 |
| RDG-00016 | partly-cloudy | 15 | PNL-P2516 | SITE-URBAN-03 | 2024-06-01T11:30:00Z | 3.82 | 17.3 | 900 | 135 | 32 | 51.5074 | -0.1278 |
| RDG-00017 | clear | 80 | PNL-Q2617 | SITE-DESERT-02 | 2024-06-01T12:00:00Z | 7.27 | 53.2 | 1740 | 200 | 12 | 25.7617 | -80.1918 |
| RDG-00018 | snow | 2100 | PNL-R2718 | SITE-HIGHLAND-02 | 2024-06-01T08:35:00Z | 2.1 | 2.5 | 730 | 0 | 60 | 60.472 | 8.4689 |
| RDG-00019 | fog | 5 | PNL-S2819 | SITE-COASTAL-02 | 2024-06-01T09:05:00Z | 0 | 7.8 | 0 | 220 | 15 | 52.3702 | 4.8952 |
| RDG-00020 | clear | 35 | PNL-T2920 | SITE-RURAL-02 | 2024-06-01T13:55:00Z | 5.22 | 27.9 | 1080 | 180 | 20 | 48.8566 | 2.3522 |
What the 200 rows show
from the 200-row sampleSnow (weather condition) stands out: mean site_
- 35median site_
elevation_ m - 3.5median output_
power_ kw - 19.2median ambient_
temperature_ c - 850.4median irradiance_
w_ m2 - 135median panel_
orientation_ deg - 27.5median panel_
tilt_ deg
Median 35, from -400 to 5,222.
- string 4
- float 8
- datetime 1
Columns
13 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 4 columns | |||
reading_id | string | Unique identifier for each solar output readingunique | RDG-00001 |
panel_id | string | Unique identifier for the solar panel | PNL-A1001 |
site_id | string | Unique identifier for the installation site | SITE-URBAN-01 |
weather_condition | string | General weather condition at the time of reading7 values · optional | clear |
| Numbers 8 columns | |||
output_power_kw | float | Measured solar panel output power in kilowatts0 or more | 4.85 |
ambient_temperature_c | float | Ambient temperature at the panel location in degrees Celsius-50 to 70 · optional | 22.5 |
irradiance_w_m2 | float | Solar irradiance at the panel surface in watts per square meter0 or more · optional | 990 |
panel_orientation_deg | float | Panel azimuth orientation in degrees (0 = North, 90 = East, etc.)0 to 359.99 · optional | 180 |
panel_tilt_deg | float | Panel tilt angle from horizontal in degrees0 to 90 · optional | 25 |
site_latitude | float | Latitude of the installation site-90 to 90 · optional | 40.7128 |
site_longitude | float | Longitude of the installation site-180 to 180 · optional | -74.006 |
site_elevation_m | float | Elevation of the site above sea level in meters-400 to 9,000 · optional | 10 |
| Dates and times 1 column | |||
timestamp | datetime | Date and time when the output reading was recorded (UTC) | 2024-06-01T08:15:00Z |
Use it for
An energy dashboard
Site_
elevation_ m by weather_ condition. Excel, Power BI or Tableau. Why do the 16 snow rows have a mean site_
elevation_ m of 2,442? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Readings200RDG-0000110clearRDG-000022200snowRDG-00003-35rain
A software demo
Believable readings with panel_
id, site_ id and timestamp to fill a screen in front of a buyer.
blueprint · energy-solar-output-time-series
Behind this dataset
Same schema. As many rows as you need.
These 200 rows came out of a blueprint — 13 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.
- Include panel ID and location
- Track hourly output
- Segment by weather condition
- Flag low-efficiency periods
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-solar-output-time-series