基于遗传算法的燃煤锅炉热效率优化  

BY USING THE GENETIC ALGORITHMS TO OPTIMIZE THE OPERATION PARAMETERS OF THE UTILITY BOILERS

作　　者：周昊[1] 朱洪波[2] 曾庭华[2] 廖宏楷[2] 岑可法[1] 

机构地区：[1]能源清洁利用和环境工程教育部重点实验室 [2]广东省电力集团公司,广东广州510600

出　　处：《中国电机工程学报》2002年第7期125-128,共4页Proceedings of the CSEE

基　　金：国家重点基础研究专项经费项目(G1999022204)。~~

摘　　要：在对锅炉飞灰含碳量进行人工神经网络建模的基础上,确定了各种运行参数和煤种对锅炉飞灰含碳量的影响关系。由于锅炉煤种的多变性,针对某个煤种进行实炉调整所获得的最佳工况往往与目前燃用煤种所需的最佳工况偏离。文中结合遗传算法和人工神经网络技术,对某台300MW四角切圆燃煤电厂锅炉热效率的优化进行了研究,为大型电厂锅炉通过燃烧调整提高锅炉效率提供有效手段。By using a neural network to model the unburned carbon content in the fly ash from a high-capacity boiler, a relationship between the unburned carbon content and the boiler operation parameters is obtained. Because of the time-to-time variation of the coal quality, however, the boiler sometimes deviates its optimal condition of operation designed for specific coal. Combining to use the neural network with a genetic algorithm, we can find the best operation parameters for getting a highest boiler efficiency. A 300MW power plant boiler is taken as an example to show the procedure of the computation and optimization, which leads to a powerful approach to promote the boiler efficiency by adjusting the boiler and its combustion in a large power plant.

关 键 词：遗传算法 燃煤锅炉 热效率 优化 

分 类 号：TK229.6[动力工程及工程热物理—动力机械及工程]