基于改进遗传算法的火电厂锅炉燃烧优化技术  

Optimization Technology of Thermal Power Plant Boiler Combustion Based on Improved Genetic Algorithm

作　　者：陈鸿 CHEN Hong(Jiangsu Guoxin Jingjiang Power Generation Co.,Ltd.,Lianyungang,Jiangsu 222023,China)

机构地区：[1]江苏国信靖江发电有限公司,江苏连云港222023

出　　处：《自动化应用》2025年第3期258-260,264,共4页Automation Application

摘　　要：火电厂锅炉燃料品质参差,直接影响燃烧稳定性与完整度,导致燃烧效率低下、污染物排放增加,因此,提出了基于改进遗传算法的火电厂锅炉燃烧优化技术。利用更完善的火电厂锅炉火焰检测技术以及改进遗传算法对燃烧预测模型进行精化,以评估煤炭质量,同时调整火电厂锅炉燃烧设备的参数,实现火电厂锅炉燃烧优化。实验结果表明,基于改进遗传算法优化后的火电厂锅炉燃烧效率可以达到97.82%,满足了火电厂锅炉燃烧需求,提升了能源的利用效率,降低了对环境的污染。The uneven fuel quality of boilers in thermal power plants directly affects combustion stability and integrity,leading to low combustion efficiency and increased pollutant emissions.Therefore,an improved genetic algorithm based combustion optimization technology for thermal power plant boilers is proposed.By utilizing more advanced flame detection technology for thermal power plant boilers and improving genetic algorithms to refine combustion prediction models,coal quality can be evaluated,while adjusting the parameters of combustion equipment for thermal power plant boilers to achieve combustion optimization.The experimental results show that the combustion efficiency of thermal power plant boilers optimized based on improved genetic algorithm can reach 97.82%,meeting the combustion needs of thermal power plant boilers,improving energy utilization efficiency,and reducing environmental pollution.

关 键 词：改进遗传算法 火电厂 锅炉燃烧 优化技术 火焰检测 

分 类 号：TK229.6[动力工程及工程热物理—动力机械及工程] TP272[自动化与计算机技术—检测技术与自动化装置]