Study on boiler’s comprehensive benefits optimization based on PSO optimized XGBoost algorithm

¹ College of Automation, Southeast University, Nanjing, China, 210000
² Jiangsu special equipment safety supervision and Research Institute Nanjing China, 210036

^* Corresponding author: guobaozh@seu.edu.cn

Abstract

To predict the boiler’s combustion efficiency and NO_x emissions, this paper introduced a particle swarm optimization optimized XGBoost algorithm. The results show that the MAPE can reach 0.107% and 3.732% respectively on the verification set, which is better SVM, LR and ANN. At the same time, this paper presents a comprehensive benefits evaluation function considering economic and environmental benefits to optimize the multi-objective optimization problem of boiler’s combustion efficiency and NO_x emission. Based on the operation data of a 300 MW Circulating Fluidized Bed, the experimental results show that: the comprehensive benefits evaluation function can reasonably balance boiler’s combustion efficiency and NO_x emissions to achieve the optimal comprehensive benefit.