Novel steam temperature control method and system based on deep learning

The invention discloses a novel steam temperature control method based on deep learning, and the method comprises the steps: building a data twinborn model based on big data, forming a data simulation body of a boiler operation state, predicting the steam temperature operation condition of a boiler, and obtaining an accurate steam temperature control parameter of a steam temperature control mechanism based on the data simulation body through employing a deep learning technology. According to the environment simulation model of the novel steam temperature control system, the fitting degree of a steam temperature prediction result and a steam temperature result of actual power generation operation within 7 minutes can be 90% or above. 本发明公开了基于深度学习的新型汽温控制方法，该方法基于大数据构建数据孪生模型，形成锅炉运行状态的数据仿真体，从而预测锅炉的汽温运行工况，再基于数据仿真体，采用深度学习技术，得到汽温控制机构的准确汽温控制参数。本发明的新型汽温控制系统的环境仿真模型能够实现7分钟之内汽温预测结果与实际发电运行的汽温结果拟合度在90％以上。