An improved Kalman particle swarm optimization for modeling and optimizing of boiler combustion characteristics

• DOI: 10.1017/s026357472200145x
• Publication Date: 2022-10-24T06:31:25Z
• Authors: Jing Liang; Hao Guo; Ke Chen; Kunjie Yu; Caitong Yue; Xia Li
• Keywords: Pulverized coal-fired boiler; Thermal efficiency

Abstract With the rapid development of national economy, demand for electricity is also growing. Thermal power generation accounts highest proportion generation, and coal most commonly used combustion material. The massive has led to serious environmental pollution. It significant improve energy conversion efficiency reduce pollutant emissions effectively. In this paper, an extreme learning machine model based on improved Kalman particle swarm optimization (ELM-IKPSO) proposed establish boiler model. modeling method applied process a 300 MWe pulverized boiler. simulation results show that compared with same type method, ELM-IKPSO can better predict thermal NOx emission concentration generalization performance. Finally, multi-objective carried out established model, set mutually non-dominated solutions obtained.