Abstract
This study presented an auxiliary system for the automatic power regulating system and operators of Lungmen nuclear power plant. The auxiliary system was design to predict and judge the plant state and to avoid improper operation. So the design system had two major functions: prediction and judgment. We used the adaptive neural fuzzy inference system to achieve the prediction function. Predicted targets are the reactor core pressure and steam flow rate of the next 5 minutes. We modularized the adaptive neural fuzzy inference system and proposed a hierarchical structures of the pressure prediction. To make the design system can judge the plant state, we used the fuzzy logic method. The output of judgment was the accept degree of the power demand. After the system was built, we used the Lungmen simulator, which is a full-scope dynamic simulator, as the test bench and the source of the training data. The auxiliary system was tested under the scenarios of the automatically increase power and the one reactor internal pump trip even. According to the result of the automatically increase power scenarios, the auxiliary system could avoid the turbine bypass value open even. Under the one reactor internal pump trip even, the input and output of the fuzzy logic could help operators to detect the abnormal state of the plant. The test result demonstrated that the design auxiliary system can make a reasonable prediction of the plant parameters in a very short time and can assist operators to improve plant safety and efficiency.