Enhancing Power Plants Safety by Accurately Predicting CO and NOx Leakages from Gas Turbines Using FFNN and LSTM Neural Networks

• Main Authors: Yousif S.T., Alnaimi F., Bazi A.A., Thiruchelvam S.
• Other Authors: 57211393920
• Format: Conference Paper
• Published: Cal-Tek srl 2024
• Subjects: Deep Learning; FFNN; Gas Leakage; LSTM; Feedforward neural networks; Forecasting; Gas emissions; Gas plants; Gas turbines; Long short-term memory; Losses; Nitrogen oxides; Deep learning; Gas leakages; Gas power plants; Natural air; Neural-networks; Plant safety; Power station; Reliable energy; Power generation
• Institution: Universiti Tenaga Nasional

Gas power plants are fast-establishing power plants capable of producing reliable energy in high watts volumes. One of its significant features is its dependency on natural air as raw material to run the gas turbine. Air passes through several stages that involve heating the air to increase its pres...