摘要
针对1000MW机组传统协调系统控制方式存在关键参数波动大、变负荷耗能大、不能很好适应煤种变化等实际问题,华能海门电厂采用Infit系统,融合预测控制技术、神经网络学习技术及自适应控制技术控制系统,使机组能在调度要求的自动发电控制变负荷速率下实现主汽压力、中间点温度等参数更优的控制品质。对比分析了关键参数运行动态特性,对同类1000MW机组运行具有一定的参考和借鉴作用。
The typical 1 000 MW power unit coordinate system has several widely-known practical problems, such as large fluctuations of key parameters, significant energy consumption under load variation, poor adaptation of coal species, and so on. However, the Infit system, which combine the predictive control technology, the neural network learning technology and the self-adaptive control technique, was used in Huaneng Haimen Power plant. Therefore, the optimal control system, includingthe optimized parameter such as the main stream pressure, mid-point temperature, are achieved. In this paper, key parameters are compared, the research results can be referenced for the operation of similar 1 000 MW power units.
出处
《电力建设》
2011年第10期71-74,共4页
Electric Power Construction
关键词
超超临界机组
协调控制(CCs)
预测控制
控制策略
ultra-supercritical power units
coordinated control system (CCS)
predictive control
control strategy