A Predictive Model for Turbine Energy Yield Estimation in a Combined Cycle Power Plant

Gas turbines are a key player in the energy generation sector and thus form a key component in energy systems as a critical infrastructure. The determination of key parameters in optimization and efficiency of the gas turbines are of utmost importance to increase their power conversion efficiency. This paper presents a simple power estimation model for a gas turbine considering all its parameters. 7412 multivariate data records from the UCI Machine Learning Repository were used in the development of a linear prediction model for estimating the turbine energy yield for a combined cycle power plant. Simulation results show that the inlet temperature of the turbine is the most critical parameter that predicts its energy yield capacity, while ambient atmospheric conditions of temperature, humidity and pressure do not predict its energy yield capacity.

https://ieeexplore.ieee.org/document/10461255