## 5 Case Study
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Monitoring Value**} & **Evaluation Result** & **Evaluation Result** & **Evaluation Result** & **Evaluation Result** \\  & **Obtained in [32]** & **Obtained in [40]** & **Obtained in [43]** & **Obtained in This Paper** \\ \hline Day 1 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 2 & Level 1 & Level 2 & Level 2 & Level 2 \\ Day 3 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 4 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 5 & Level 1 & Level 2 & Level 2 & Level 2 \\ Day 6 & Level 1 & Level 2 & Level 2 & Level 1 \\ Day 7 & Level 1 & Level 2 & Level 2 & Level 1 \\ Day 8 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 9 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 10 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 11 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 12 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 13 & Level 2 & Level 2 & Level 2 & Level 2 \\ Day 14 & Level 2 & Level 2 & Level 2 & Level 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 13: The comprehensive power quality evaluation results with different methods. Figure 6: The results of synthetic evaluation of steady-state power quality. As shown in Table 13, the comprehensive evaluation results of power quality obtained by the method proposed in this paper are basically consistent with those obtained by several other methods, which proves the feasibility of the method proposed in this paper. When conducting comprehensive power quality assessments for different monitoring points, the PPIs of the level upper boundary value also changed. This is because we calculated the PPIs by calculating the level upper boundary value and monitoring value together. It is apparent that altering the weights of indices will change the PPIs, and the results of evaluation may also change. To illustrate, we conducted a comprehensive sensitivity analysis by studying the following six cases. Case 1-6: A dominant interval weight \(\left(0.4\quad 0.5\right)\) is assigned to an index, and an equal interval \(\left(0.1\quad 0.2\right)\) is assigned to the other five indices (Case 1 means the dominant interval weight is assigned to \(x_{1}\)). Here, we take a new style to describe the level of power quality by Equation (41). \[\text{Level}=m+\frac{PPI_{day}-PPI_{lv,m}}{PPI_{lv,m+1}-PPI_{lv,m}},m=1,2,3,4 \tag{41}\]  
where \(PPI_{day}\) is the PPI value of a certain day, \(PPI_{lv,m}\) is the PPI value of the \(m\)th level upper boundary in Table 2, and \(PPI_{lv,m}\) is determined based on the constraints of Equation (42). \[ \begin{array}{l}\min\left|PPI_{day}-PPI_{lv,m}\right|\\ s.t.\quad PPI_{day}>PPI_{lv,m}\end{array}  \tag{42}\]  
If \(PPI_{day}<PPI_{lv,1}\), the level of power quality can be by determined by Equation (43). If \(PPI_{day}>PPI_{lv,5}\), we directly identified it as unqualified. \[\text{Level}=\frac{PPI_{day}}{PPI_{lv,1}} \tag{43}\]  
The level here may not be an integer, and the results of sensitivity analysis are presented in Figure 7. We can see that the evaluation results vary with the change of the weights of the six indicators. Therefore, the accurate determination of the weights of the indicators is critical for determining the synthetic evaluation result accurately.