# Sustainable Operation of Active Distribution Networks
## 4 Case Study
The active power the distribution network exchanges with the main electric grid both in its optimal and business as usual operation is given in Figure 8:1 The proposed method aims to reduce the overall operation cost of the ADN by shifting the power demand in time periods with low electricity price. It was verified in the optimal operation scenario that the main electric power grid supplies the ADN with large amounts of power when the electricity price is low, while the opposite happens when the electricity price is high. Detailed simulation results showed that significant cost reduction in the range of 17% was achieved by the application of the suggested optimization algorithm in comparison with the business as usual operation scenario of the ADN. Therefore, as shown in Figure 19, although there were time periods when the active power exchanged between the ADN and the main electric grid received higher values in the optimal operation scenario in comparison with the business-as-usual scenario, the total ADN's operation cost was significantly reduced at the end of the 24-h time period. Moreover, the obtained results show that the total active energy the ADN needs to absorb from the main electric grid to meet its 24-h energy demand is reduced in the range of 6.18%, when the suggested optimization technique is applied compared to the typical operation scenario of the ADN. The major information of the obtained cost resulting from the execution of the examined operation case studies is tabulated in Figure 8:2 A significant cost reduction of 2478 m.u./day was achieved as a result of the implementation of the suggested optimization algorithm in comparison with a typical operation of the ADN. In addition, when the uncertainty of the ambient temperature and the electricity price were taken into consideration, and a slight increase of 0.92% in the daily operation cost of the examined system was observed. The proposed method only requires one round of communications between the agents. It was proven that the total time required for the computations and communications is very low, rendering the suggested method ideal for real-world applications in distribution networks hosting large building prosumers and PEVs. A typical average agent to agent communication latency is 0.15 s according to [31]. The required computation time to \begin{table}
\begin{tabular}{c c c c} \hline
**Operation Case Study** & **Optimal without Uncertainty** & **Optimal with Uncertainty** & **Typical** \\ \hline
**Total operation cost (m.u./day)** & 12,333 & 12,446.5 & 14,812 \\ \hline \end{tabular}
\end{table} 
Table 2: Examined operation case studies. Figure 19: The total ADN’s active power in both the optimal and typical operation. model the buildings' loads in this study was 0.1 s. Moreover, the execution of the optimal operation scheduling of the examined ADN requires on average 1517.2 s. Based on the aforementioned, the maximum expected time for the calculations and communications was \(T=4\times 0.15\) s + 2 \(\times\) 0.1 s + 1517.2 s = 1518 s, which is absolutely satisfactory for the day-ahead operation scheduling of such complex ADN.