Research on forecasting approach of key parameters of PWR pressurizer water level

Abstract

Nuclear power has special safety requirements and must be generated on the premise of nuclear safety. It is necessary to forecast the abnormal situation of system and equipment as soon as possible, so we can control the accident beforehand and prevent the nuclear safety risk caused by the failure and accident. At present, the pre-accident control method in nuclear power plant mainly relies on the subjective experience of personnel. In contrast, intelligent forecasting and timely reasoning of the change trend and possible impact of the key safety-related parameters in nuclear power plant can bring data reference to the staff of the power plant, help to control the accident before it happens and effectively reduce the probability of accident occurrence. In PWR(Pressurized Water Reactor), safety is closely related to the key parameters of primary loop such as pressurizer water level. Adequate water level of pressurizer is the key to ensure the normal discharge of reactor heat, and abnormal changes of pressurizer water level may lead to nuclear accidents. Therefore, our paper analyzes and models the water level control function of the pressurizer in PWR, the operation history of nuclear power plant related to this function is collected as well. Then a network model is built based on transformer to do information mining, which can successfully forecast the trend of key parameters related to pressurized water level and provides reference information for staff.