A Performance Evaluation Method of Coal-Fired Boiler Based on Neural Network

Abstract

According to the evaluation and control of energy-saving and emission reduction performance of coal-fired boilers, the performance indexes of boiler combustion and emissions were studied, and a performance evaluation and control method based on neural network was proposed. Firstly, the influencing factors of boiler combustion emission are analyzed. A boiler combustion emission evaluation model based on AdaBoost-BP algorithm is designed. The model is trained and tested by coal-fired power plant data and national emission standards, and the principal component analysis method is adopted. The core parameters are adjusted to get the best control solution. Finally, experiments show that the model and method have better advantages in comparison with similar methods.