metadata
license: gpl
dataset_name: nigerian_energy_and_utilities_turbine_generator_sensors
pretty_name: Nigerian Energy & Utilities – Turbine/Generator Sensors
size_categories:
- 10K<n<1M
- 1M<n<10M
task_categories:
- time-series-forecasting
- tabular-regression
- other
tags:
- nigeria
- energy
- utilities
- power
- grid
- smart-meter
- renewables
language:
- en
created: 2025-10-10T00:00:00.000Z
# Nigerian Energy & Utilities – Turbine/Generator Sensors
Turbine/generator sensor logs (RPM, temperatures, vibration) with alarms per condition limits.
- **[category]** Power Generation
- **[rows]** ~200,000
- **[formats]** CSV + Parquet (snappy)
- **[geography]** Nigeria (DisCos, substations, plants)
## Schema
| column | dtype |
|---|---| | timestamp | object | | plant_id | object | | unit_id | object | | rpm | float64 | | shaft_temp_c | float64 | | bearing_temp_c | float64 | | vibration_mm_s | float64 | | alarm | bool |
## Usage
```python
import pandas as pd
df = pd.read_parquet('data/nigerian_energy_and_utilities_turbine_generator_sensors/nigerian_energy_and_utilities_turbine_generator_sensors.parquet')
df.head()
```
```python
from datasets import load_dataset
ds = load_dataset('electricsheepafrica/nigerian_energy_and_utilities_turbine_generator_sensors')
ds
```
## Notes
- Data generated with Nigeria-specific parameters (DisCos, tariff bands, 50 Hz grid)
- Time-of-use shapes and seasonal/weather effects included where applicable
- Values are internally consistent (e.g., kWh ~ kW*h; voltage/current ~ power)