【摘要】 大型燃煤电厂锅炉热效率目前通常依靠燃烧试验调整优化,现场试验耗时费力,而且由于锅炉输入输出特性复杂,耦合性强,燃用煤种和操作条件变化较大,通过试验进行燃烧优化往往效果不佳。介绍开发的一种设计软件,它利用人工神经网络对锅炉特性建模,并采用遗传算法进行最佳运行工况寻优,可获得目前最佳的锅炉燃烧调整方式,实现锅炉的节能降耗。更多还原

【Abstract】 The heat efficiency of large size coal-fired utility boilers is usually optimized by using combustion test and adjustment, the word is heavy and time-consuming. Because the input and output characteristics of boiler are complicated, the coal rank and boiler operating conditions change often, and the coupling effect is strong, so the results of: combustion optimization through tests are not so good often. This paper introduces a kind of developed design software, which uses artificial neural network to set up a boiler property model, and employs genetic algorithm to optimize the working conditions, so as to obtain currently optimum combustion adjustment mode of boiler, with energy saved and consumption reduced.更多还原