核电站凝水系统的状态预测方法研究

Abstract

运行支持系统可以辅助操纵员进行决策分析，对于提高核电站的安全性和可靠性具有重要意义。而发生故障后的状态预测方法是目前运行支持技术中的热点问题，本文提出基于机理仿真的凝水系统状态预测方法。在进行故障特性分析的基础上，将从仪控系统中采集到的实际测量数据引入机理仿真过程中，在核电站正常运行时仿真模型能与之同步运行；当电站发生故障后，能快速完成异常的识别并切换至超实时运行进行运行状态预测。通过采集600 MW全范围仿真机中的正常和故障数据进行实验测试表明，本方法可以实现有效的状态预测，可以辅助操纵员评估故障的发展变化趋势和严重程度。 Operation support system can improve the safety, reliability and economy of nuclear power plant, condition forecasting technology is one of the hot research problems in operation support system. The major work of this thesis is researching the technology of condition forecasting of condensate water system. By a detailed analysis of the composition and the failure characteristics of the condensate water system, the paper uses the simulation model to predict the condition of the equipment. When the equipment is in normal, the system can simulate the current state in realtime; when the failure occurs, the condition forecasting module based on simulation model run in ultrareal time to predict the future states and anomalies of the equipment. The method has been proven by simulation validation. Results show that the condition forecasting system meets the requirements of predicting the state of nuclear power plants, and provides sufficient information for the operators.