## 5 Results and Discussion  
### General Computing Overview  
The data reconciliation model used in this paper is based on design values of the system. The known variables of data reconciliation are given by adding certain random errors to the characteristic data and measurement data under the design condition, and the subsequent iterative calculation process of data reconciliation is carried out. The known variables with random errors can be represented here as follows:  
\[x_{i}=x_{i,0}+\sigma_{x,i}\cdot\varphi \tag{19}\]  
where \(x_{i,0}\) is the design value corresponding to the known variable \(x_{i}\) and \(\varphi\) is the coefficient of random errors. Here, for the random error coefficient, the uniform distribution in \([-1,1]\) is taken to enhance the convergence of the data reconciliation calculation process. For gross errors, it is necessary to add a gross error much larger than \(\sigma_{x,i}\) on the basis of the corresponding design value of the known variable. The data reconciliation model in this paper calculates ten groups of working conditions. Among them, the first two working conditions do not contain gross errors, and the last eight working conditions all contain one to four gross errors. The specific working conditions are set as shown in Table 6. Among them, Conditions 1 and 2 only contain automatically generated random errors, the purpose of which is to study the reconciliation ability and effect of the data reconciliation model without gross errors. Condition 3 to Condition 6 add one gross error of temperature, pressure or mass flow sensor, respectively, and Condition 7 to Condition 10 add two to four grossa errors, respectively, to study the \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Parameter** & **Reference Model** & **Present Model** & **Deviation** \\ \hline \multirow{4}{*}{Output Value} & SC mass flow of CO\({}_{2}\) (kg/s) & 132.53 & 133.420 & 0.67\% \\  & AC consumption power (kW) & 40,014 & 39,817 & 0.49\% \\  & GT output power (kW) & 70,997 & 71,129 & 0.19\% \\  & ST1 output power (kW) & 9490 & 9553 & 0.66\% \\  & ST2 output power (kW) & 6733 & 6777 & 0.65\% \\  & SC consumption power (kW) & 3457 & 3480 & 0.67\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: _Cont._ \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Stream Number** & **Parameter** & **Design Value** & **Reconciliated Value** & **Deviation** \\ \hline Stream 9 & H cold side output temperature (\({}^{\circ}\)C) & 517.600 & 517.600 & 0 \\ Stream 10 & STI output temperature (\({}^{\circ}\)C) & 390.330 & 389.086 & 0.31\% \\ Stream 12 & LTR hot side inlet mass flow (kg/s) & 132.530 & 133.419 & 0.67\% \\ Stream 15 & SC output temperature (\({}^{\circ}\)C) & 62.690 & 62.690 & 0 \\ Stream 16 & H cold side inlet mass flow (kg/s) & 69.890 & 70.357 & 0.67\% \\ Stream 17 & LTR cold side inlet mass flow (kg/s) & 62.640 & 63.062 & 0.67\% \\ Stream 18 & HTR cold side inlet temperature (\({}^{\circ}\)C) & 255.470 & 255.470 & 0 \\ Stream 19 & HTR cold side output temperature (\({}^{\circ}\)C) & 380.330 & 380.325 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Verification results of data reconciliation model under the design condition. model ability of identifying suspicious sensors with gross errors and reconciliating of the overall system parameters under the condition of gross errors. Under the above ten working conditions, the quality factors of the system in the data reconciliation calculation process which is defined in Equation (15) are shown in Figure 2. The quality factors of ten working conditions are all less than 1, which meets the requirements of global gross error inspection. Quality factor is a test statistic that characterizes whether there are serious errors within the whole system [37]. Only when it is less than 1 it can be indicated that it has passed the global inspection, which means the calculation of the system model does not contain serious errors at the system level. In addition, the quality factors of Conditions 1 and 2 which do not include gross errors are about 0.2.