Solar Generation and Maintenance Dataset
Compare generation normalized for capacity and inspect maintenance costs.
A practical workbook exercise for asset analysts and maintenance coordinators. Work from the underlying records, compare the relevant totals and explain how you reached your result.
About the dataset
This original synthetic dataset contains 1,164 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Renewable energy projects |
| Formats | Excel workbook and CSV files |
| Source records | 1,164 |
| Related tables | 3 |
| Fields across table schemas | 15 |
| Reporting cutoff | September 30, 2026 |
| Currency | USD for monetary fields |
| Source | Original synthetic data created for Jolene.pro Workbook Studies |
What's included
- Assets: 12 records and 4 fields. One solar site with nameplate kW capacity and fixed USD/kWh tariff.
- Generation: 1,104 records and 5 fields. One site-day generation record.
- WorkOrders: 48 records and 6 fields. One maintenance work order.
Recommended analysis
- Which sites have the lowest kWh per installed kW?
- How much of generation is estimated?
- What maintenance cost is recorded per site?
- Can maintenance timing alone establish lost generation?
How to work with the data
Use the following relationships to connect the source tables:
- Generation.asset_id → Assets.asset_id
- WorkOrders.asset_id → Assets.asset_id
Check the row grain before joining. Aggregate repeated child records to the required level before combining totals, so parent amounts are not counted more than once.
You can explore the workbook in Excel or Jolene.pro, or use the CSV files with SQL, Power BI and other analysis tools.
Definitions and assumptions
- Generated kWh × tariff estimates contracted energy value, not invoiced cash or accounting revenue.
- Weather, grid curtailment and comparable irradiance are absent. Do not infer causal equipment underperformance from generation alone.
Use the field definitions and nullable-column guidance in the included data dictionary. Interpret blank values and reporting dates according to the scenario notes.
Downloads
The complete dataset ZIP includes the Excel workbook, three matching CSV files, a data dictionary, scenario notes, a source-row preview and license details.
Reuse and attribution
These are synthetic records, not customer data or industry benchmarks. Reuse is allowed under Creative Commons Attribution 4.0 International (CC BY 4.0). Credit Jolene.pro and identify any changes you make.