ANN-weighted Distance Grey Wolf Optimizer for NOx Emission Optimization in Coal Fired Boilers of a Thermal Power Plant - Malik, Mahmad Raphiyoddin Shaphiyoddin; Priya, Viswambaran Saraswati (Engineering, Technology & Applied Science Research, 2024)
This research work suggests the application of predictive modeling for the Nitrogen Oxide (NOx) emissions from the 210 MW pulverized boiler that burns coal. In order to lower the NOx emissions in the flue gas, it is necessary to optimize various operational parameters during combustion, including oxygen in flue gas, various damper opening positions, air-distribution system, nozzle tilt, and the temperature of the flue gas outlet. Information gathered from variable parametric field tests was used to create an Artificial Neural Network (ANN) model. The model estimated NOx emissions based on the parameters of coal combustion. The ANN model was put to the test under full load conditions and the results of its predictions were compared to the actual values. The trained ANN with its biases and weights in the form of arithmetical equations was given as a fitness function to the weighted distance Grey Wolf Optimizer (GWO) to improve operating conditions for decreased NOx emissions.