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An Interpretable Catboost Model to Predict the Power of Combined Cycle Power Plants

As worldwide energy demand continues to rise, the importance of combined cycle power plants is growing. Therefore, the task of predicting the power generated by a combined cycle power plant is a very significant one. In this study, a Catboost model which can predict the electrical energy output (EP) of a combined cycle power plant is presented. The Root Mean Square Error (RMSE) value achieved with the Catboost model is 0.0678, that is outstandingly lower in comparison with other methods in existing literature. Finally, Shapley additive explanations (SHAP) were employed to explain the inner workings of the Catboost model and how the factors impacted the model’s decision making process were figured out.