基于机理仿真拓展的电厂热力系统数据代理映射模型构建方法

A Data Surrogate Mapping Model Construction Method for Power Plant Thermal System Based on Mechanism Simulation Extension

电厂系统高精度映射模型是智慧电厂先进调度控制的核心技术,传统现场试验获取数据的方法成本高、时间长,而在线机理模型仿真依赖高成本的仿真系统。文中提出一种基于机理仿真拓展的电厂热力系统数据代理映射模型构建方法。首先离线建立热力系统的结构机理映射模型,通过有限试验工况的运行数据对模型进行辨识修正;构建所需多工况条件,采用仿真系统运行高精度机理映射模型获得拓展的多工况运行样本数据;基于多工况运行样本数据,采用数据建模方法建立热力系统的数据代理映射模型,并脱离机理仿真系统加以运用。以某热电联产机组为案例的分析表明,基于神经网络建立的数据代理映射模型与机理映射模型计算结果的误差在1%以内,具有较高的一致性。

High-precision mapping model of the power plant system is the core technology of advanced scheduling and control in smart power plants. The traditional method of obtaining data through field tests is costly and time-consuming. Meanwhile, online mechanism model relies on expensive simulation software. This study proposed a construction method of data surrogate mapping model of the thermal power plant system based on mechanism simulation extension. Firstly, an offline structural mechanism model of the thermal system was established, and the model was identified and modified by the operating data of the limited experimental conditions. Based on that, the necessary multiple working conditions were constructed, and the corresponding data were thereafter obtained through simulation of the mechanism model. Finally, the data surrogate mapping model of the thermal system was established based on the data of multiple working conditions, and could be used without a mechanism simulation system. The analysis of a combined heat and power unit shows that the error between the neural network data surrogate mapping model and mechanism model is less than 1%, justifying that the proposed approach has high accuracy.