## 5 Case Study
### Influence of Distributed Power Supply and Load Uncertainty on System Dispatchability Index  
In EGCS, there are load problems with uncertainties and distributed power whose output is uncertain due to the influence of the natural environment. Because distributed power is connected to the side of the grid, only two cases are set under the standard case 30 network to study the impact of distributed power uncertainty and load uncertainty on system dispatchability indexes.  
Case 1: There is no distributed power access in the system. If the load obeys the normal distribution where the mean value is the initial value and the variance is 0.02 times the mean value, the reliability level of the system is set to 1.5.  
Case 2: There is distributed power access in the system and load uncertainty is not considered. The predictive error parameters of wind farms and photovoltaic plants are listed in Figures 11 and 12 in Appendix A, and the reliability level of the system is set to 1.5.  
The system running cost under case 1 is $1384.36, and case 2 is $1157.91. We can conclude that the total running cost of the system can be effectively reduced by accessing distributed power. The comparison of dispatchability margin between the two cases is shown in Figure 16.  
As can be seen from Figure 16, the system dispatchability margin index is higher in both case 1 and case 2 because of the sufficient capacity of case 30-node generators. There are several moments in  
Figure 16: Effect of distributed power and load uncertainty on system dispatchability margin.  
Figure 15: Prediction of wind farm output photovoltaic plant.  
both cases when the index values are higher than other values, such as 04:00 and 23:00 in case 1. It should be noted that the dispatchability margin index at that time is the downward dispatchability margin index, while at other times, the index is the upward dispatchability margin index, which indicates that the downward dispatchability margin of the system is higher than that of the upward dispatchability margin.  
The dispatchability margin of the system in case 1 is always generally higher than that in case 2, which shows that the uncertainty of load will not have a great impact on the dispatchability of the system. In this case, it is only necessary to consider whether the backup capacity of the system meets the dispatching requirements on a single time section. However, for distributed generation, after wind power and photovoltaic power are connected, the influence of multi-time scale correlation of wind power and photovoltaic power prediction error on system dispatchability index should be considered.  
Between 01:00 and 06:00, the dispatchability margin index of the system is generally high and basically stable. The reason is that in the early morning, the load of the system does not change much on the horizontal time scale. The reason that the dispatchability margin of case 2 differs greatly on the time scale should be affected by the prediction error of the distributed power output. Between 11:00 and 14:00, the system dispatchability margin index in case 1 has little change compared with the previous period, while in case 2, because the output of photovoltaic plant is higher during this period, the prediction error is also larger, so the system dispatchability margin index will be lower than the previous period.