Performance of a Pressurized Water Reactor Power Estimation Algorithm

The performance of a Kalman filter that estimates core power in a pressurized water reactor was evaluated using data from the Loss of Fluid Test (LOFT) Reactor and linear error analysis techniques. The Kalman filter provides a more accurate core power estimate in real time than does the conventional method of power estimation. Accuracies of better than 0.75% of rated power are obtained with the Kalman filter. If this accuracy improvement can be translated into higher levels of power operation, then more revenue can be generated by a commercial power plant. Scaling the LOFT 150-MW(thermal) l accuracy improvement up to a 1000-MW(electric) commercial power plant size, assuming that average power production is increased by the amount of the accuracy improvement, results in more than $800 000 of extra revenue per year ($0.06/kW·h).