# WAMS-Based Online Disturbance Estimation in Interconnected Power Systems Using Disturbance Observer
## 5 Simulation Results and Discussions
### Disturbance Estimation for the Whole Combined Areas Using the Disturbance Observer  
In contrast to the decentralized monitoring scheme, based on WAMS, monitoring for the whole power system can also be done in real time at a control center. To achieve this a 16 \(\times\) 16 matrix for the whole power system is developed. The power system matrix A and the disturbance matrix F are then used in the design of the disturbance observer. To show the efficiency of this method, four different disturbance scenarios are simulated and evaluated. The four simulated scenarios are aimed at showing that the observer can accurately estimate single disturbances and multiple disturbances occurring at the same time or at different times. From Table 2 it can be seen that in scenario 1 a large disturbance of magnitude 0.1 p.u occurred only in area 1. The estimation is given in Figure 8a,b, it can be seen that the observer took approximately 2.5 s to accurately estimate the disturbance. In scenario 2, two disturbances of magnitude 0.01 p.u and 0.05 p.u occurred at \(t=1\) and \(t=5\) in area 1 and 2 respectively. Figure 9a,b show that it took 1.5 s to estimate disturbance in area 1 and 2.5 s in area 2.  
In scenario 3 a large disturbance occurred at \(t=1\) in area 3 and a medium disturbance occurred in area 4 at \(t=5\). Figure 10a,b show that it took 3 s to estimate the disturbance in area 3 and less than a 1 s to estimate the disturbance in area 4. The power system under investigation is an interconnected power system consisting of several control-areas. In the aforementioned figure, a 0.1 p.u. disturbance occurred in area 3 at time \(t=1\) s, then at time \(t=5\) s another disturbance with magnitude of 0.05 p.u. occurred in area 4. Due to the natural interconnection between these areas by the major tie-lines, a dipping in the estimated disturbance in area 3 at \(t=5\) s has occurred. This dipping would not affect the estimation and does not have bad consequences since the operator at the control center can monitor this situation and can observe the disturbances in all areas simultaneously.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Scenario**} & \multicolumn{2}{c}{**Area\#1**} & \multicolumn{2}{c}{**Area\#2**} & \multicolumn{2}{c}{**Area\#3**} & \multicolumn{2}{c}{**Area\#4**} \\  & \(\Delta P_{1}\) & \(t_{1}\) & \(\Delta P_{2}\) & \(t_{2}\) & \(\Delta P_{3}\) & \(t_{3}\) & \(\Delta P_{4}\) & \(t_{4}\) \\ \hline \(S_{1}\) & 0.1 & 5 & 0 & 0 & 0 & 0 & 0 & 0 \\ \(S_{2}\) & 0.01 & 1 & 0.05 & 5 & 0 & 0 & 0 & 0 \\ \(Figure 8: Scenario 1: (**a**) estimated disturbances and (**b**) actual vs. estimated disturbances.  
Figure 9: Scenario 2: (**a**) estimated disturbances and (**b**) actual vs. estimated disturbances.  
Finally, in scenario 4 a large and medium disturbances occurred in area 1 and area 4 respectively, both at \(t=1\). From Figure 11a,b, it took only 1.5 s in both cases to estimate the disturbance. It is also important to note that due to power line deviations in cases of two disturbance occurring at different times, the observed disturbance for the first occurred disturbance will drop then quickly return to its actual value.  
Figure 11: Scenario 4: (**a**) estimated disturbances and (**b**) actual vs. estimated disturbances.  
Figure 10: Scenario 3: (**a**) estimated disturbances and (**b**) actual vs. estimated disturbances.