Abstract
The nuclear fuel rods of the nuclear power plant are both the source of energy and radiation. Therefore, the thumb rule for the power ascension operation is to bring up the power to the rated level as efficiently as possible, however under the premise of fuel integrity, to maximize economic benefits. To ensure the fuel rod integrity at all time, including normal operation, anticipated transient operation, and loss of coolant type of accident, the crucial operational parameters such as minimum critical power ratio, maximum linear heat generation rate, maximum average planar linear heat generation rate, power oscillation, etc., must be kept within the operation limit value which are more restrict and conservative than safety limit value. It is difficult to complete the aforementioned task because of the complicated characteristics of the boiling water reactor core, such as relationship between temperature, void and reactivity, local power distribution and xenon transient. There is no standard operating procedure to guide the operator in performing control rod withdrawal and core flow rate changes; operators must determine their actions with on-site measurements and experiences, and these actions often lead to operational difficulties. As a result, the power ascension strategy differs by each operator. In addition to the extra work load, some operators may be too aggressive to narrow the safety margin, or too conservative to delay the power ascension process which is not economic and efficient. A pre-defined power ascension path will be beneficial to the operators. To overcome the above issue, the Simulate-3 code was used to calculate the reactor core status. The requirements of power ascension path was formulated by fitness function as an optimization problem with power ascension time, thermal limits, core stability and maximum rod line, as the constraints. Being an efficient and stable global search algorithm, the genetic algorithm was adopted to search for the optimized power ascension path. The fitness value was based on the core status calculated by Simulate-3, which was very time consuming. To reduce the effort, this study incorporated in experts’ operation experience to define the preliminary constraints of power ascension parameters （control rod position and core flow）to confine the searching domain by eliminating some improper solutions that were against the operation requirement, and the offline-trained artificial neural network（ANN）selector was introduced to screen the power ascension path by excluding the improper solutions from further evaluations. The input vector’s dimension of ANN was relatively large, so that principal component analysis（PCA）is utilized to reduce the dimension. As the result, the ANN training became more efficient, and the pattern recognition capability was improved as well. In summary, the research combined the multi-object optimization of GA, pattern recognition of ANN and dimension reduction of PCA to search for the optimized power ascension path of boiling water reactor （BWR）. The simulation results showed that the developed algorithm can obtain the adequate power ascension path at beginning, middle, and end of cycle.