为解决热电厂机组间负荷分配不合理的问题，提出一种基于模型预测的多模式供热电厂多机组间负荷实时优化分配方法。基于模块化建模原理构建热电厂全厂范围的机理仿真模型,并运用运行数据对模型辨识校准，根据机组特性和电网调峰补贴政策，建立全厂的运行经济性收益评估模型，进而设计基于粒子群算法的负荷实时优化方法，借助性能预测模型预测评估各方案的经济性。以某包含高背压、切缸、抽汽、光轴4种供热模式机组的电厂为例，对不同电、热负荷组合工况下的厂内负荷进行优化分配研究。应用结果表明：该方法可根据热、电负荷的实时指令在线获得经济性优化的厂内机组间负荷分配方案。

In order to solve the problem of unreasonable load distribution among thermal power plant units, this paper presents a realtime optimal load distribution method based on model prediction for multiple heating units in multimode thermal power plant. A factorywide mechanism simulation model is constructed based on modular modeling principle, and the model is identified and calibrated by using operation data. According to the characteristics of the unit and the peak shaving subsidy policy, the evaluation model of the operation economic benefits of the whole plant is established. Furthermore, a realtime load optimization method based on particle swarm optimization algorithm is designed, and the economy of each scheme is predicted and evaluated with the help of performance prediction model.Taking a power plant with 4 heating modes including high back pressure, cylinder cutting, steam extraction and plain shaft heating units as an example, the optimal distribution of load in the plant under different electrical and thermal load combinations is studied.The application results show that the proposed method can obtain the economical optimal load distribution scheme among plant units online according to the realtime instructions of thermal and electrical loads.

TM621

国家重点研发计划（2019YFE0126000）