Summary: The dataset contains 9568 data points collected from a Combined Cycle Power Plant over 6 years (2006-2011), when the plant was set to work with full load.
| Parameter | Value |
|---|---|
| Name | Combined Cycle Power Plant |
| Labeled | Yes |
| Time Series | No |
| Simulation | No |
| Missing Values | No |
| Dataset Characteristics | Multivariate |
| Feature Type | Real |
| Associated Tasks | Regression |
| Number of Instances | 9568 |
| Number of Features | 4 |
| Date Donated | 2014-03-25 |
| Source | UCI Machine Learning Repository |
The dataset contains 9568 data points collected from a Combined Cycle Power Plant over 6 years (2006-2011), when the power plant was set to work with full load. Features consist of hourly average ambient variables Temperature (T), Ambient Pressure (AP), Relative Humidity (RH) and Exhaust Vacuum (V) to predict the net hourly electrical energy output (EP) of the plant. A combined cycle power plant (CCPP) is composed of gas turbines (GT), steam turbines (ST) and heat recovery steam generators. In a CCPP, the electricity is generated by gas and steam turbines, which are combined in one cycle, and is transferred from one turbine to another. While the Vacuum is collected from and has effect on the Steam Turbine, the other three ambient variables affect the GT performance. For comparability with our baseline studies, and to allow 5x2 fold statistical tests to be carried out, we provide the data shuffled five times. For each shuffling, 2-fold CV is carried out and the resulting 10 measurements are used for statistical testing. We provide the data both in .ods and in .xlsx formats.
Power plant, Energy output, Regression tasks, Environmental data, Multivariate data