The operation of a pressurized water reactor requires an estimate of average core power. If there is uncertainty in the power estimate, the plant must be operated at a reduced power level to ensure that safety-related indexes are not exceeded. Thus, power estimate uncertainty results in decreased energy production. A Kalman filter has been designed to combine information from several sources and thereby reduce power estimation errors. The investigation provides three primary results. First, clearly defined instrument-error models are specified and the need for these models becomes clear. Second, the investigation shows that the sensitivity to unexpected errors can be reduced by utilizing information from more than one source. Third, calculations for a hypothetical 1000-MW(electric) power plant that sells electrical energy for $0.06/kWh show that an additional annual revenue of approximately $1 million can be realized by applying the Kalman filter. A few calculations are the only investment needed to obtain the additional revenue.