power_plant.txt

- 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 (C), Ambient 
Pressure (ATM), Relative Humidity (%) and Exhaust Vacuum (Torr) to predict the net hourly 
electrical energy output (EP, MJ)  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 of the ambient variables effect the GT performance.

- For comparability with our baseline studies, and to allow 5x2 fold statistical tests be
carried out, we provide the data shuffled five times. For each shuffling 2-fold CV i
carried out and the resulting 10 measurements are used for statistical testing.

We provide the data both in .ods and in .xlsx formats.

Relevant Papers to cite:

Pınar Tüfekci, Prediction of full load electrical power output of a base load operated
combined cycle power plant using machine learning methods, International Journal of
Electrical Power & Energy Systems, Volume 60, September 2014, Pages 126-140, ISSN 
0142-0615, http://dx.doi.org/10.1016/j.ijepes.2014.02.027.
(http://www.sciencedirect.com/science/article/pii/S0142061514000908)

Heysem Kaya, Pınar Tüfekci , Sadık Fikret Gürgen: Local and Global Learning Methods for
Predicting Power of a Combined Gas & Steam Turbine, Proceedings of the International
Conference on Emerging Trends in Computer and Electronics Engineering ICETCEE 2012, pp.
13-18 (Mar. 2012, Dubai)