With more extensive applications of supercritical carbon dioxide in the design of thermal systems

it becomes necessary to explore the methods for handling measurement errors and evaluating the thermo-economical performance of the systems in the actual operations. The paper takes the supercritical carbon dioxide recompression cycle thermal system as the research object

and proposes an iterative data reconciliation algorithm that can solve the unknown variables as well as their uncertainties. The algorithm is applied for the exergy analysis of the thermal system. The analysis results on 10 groups of working conditions with random errors and 5 other groups with instrument faults show that the method proposed in the paper can effectively reduce the residuals of system constraints and measurement deviations from the sensors

decrease the calculation errors of the units' exergy losses

and therefore increase the accuracy of the system thermal economy figures. Through data reconciliation

the errors of round trip thermal efficiency and exergy efficiency of the system can be reduced from a peak of 14.65% down to 1.04%

which proves that data reconciliation method is capable for improving the accuracy in evaluating the operational state of real thermal systems.