## 5 Performance Evaluation  
The implemented scenario is tested in a modified IEEE 34 node system model with distributed energy sources. Figure 1 illustrates the proposed microgrid scenario. The highest priority customers are located at Buses 802, 822, 830, 840, 860 and 890. A communication network covers all the geographical area of the IEEE 34 bus system. The network is designed and implemented with LTE technology and, as a way to ensure a reliable microgrid operation, the communication loads are connected to the system together with the other system loads in their equivalent buses. The EMS adapts the communication power consumption according to the operational state of the microgrid. In this way, during the operation of the system, it is guaranteed minimum connectivity even though severe saving actions have been taken. Table 5 lists the values of the DERs, which supply the system, and the capacity of each energy storage system (ESS). Figure 1: Modified distribution system model with distributed energy resources. Due to the large geographical area in the modified IEEE (Institute of Electrical and Electronics Engineers) 34 node system, the system is divided into two regions because of the system characteristics. The real geographical conditions, with one being a low-density rural area and the other a high-density urban area in the system, made this division feasible. In the application carried out here, it was interesting, since the two regions considered present different characteristics, enabling us to test the potentiality of the proposed methodology. The microgrid is disconnected from the main grid at 10 a.m. due to any event or failure, the breaker at feeder 800 will open, and DERs are going to supply the system. Figure 2a shows the power consumption over time obtained using both the previous methodologies and the hybrid method proposed in this study. The comparison of the results helps to understand the effect of considering the communications' energy consumption in an islanded operation scenario. In [24], the EMS is developed without regard to the communication network as a proper load. Therefore, its results (see dotted black line) are incomplete, and any comparison with the proposed methodology is unfair since the system is less loaded. However, comparing both results in Figure 2a, with a full active wireless system and without considering it (see dotted black line and dotted blue line), the influence of telecommunications energy consumption is remarkable in the grid's survival time. Communications power consumption dramatically harsh the system and its impact cannot be discarded to ensure a real-time operating system. The method reported in [25] considers the communication network as a proper load. The vast amount of communication load are calculated from Equation (1) and considered a high rank load. This approach is not efficient, as the network is going to be continuously available for the whole area, even though only a small area needs connectivity. In addition, in [25], the same case is investigated considering the application of soft sleep mode. The power amplifiers are turned off during most of the time. This fact produces a distinct improvement on the maximum available time to supply the loads (compare dotted blue line with dotted red line), the microgrid is provided for 90 min more with soft sleep modes, since the PA consumes an enormous amount of energy in a base station unit. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Node** & **DERs, Types** & **Power/Energy Capacity (kW/kWh)** \\ \hline
800 & Valve-Regulated Lead-Acid Battery Energy Storage System & 1000/3000 \\ \hline
810 & Backup Diesel Engine & 64 \\ \hline
820 & Photovoltaic Power & 60 \\ \hline
828 & Wind Power & 60 \\ \hline
856 & Photovoltaic Power & 280 \\ \hline
864 & Wind Power & 330 \\ \hline
890 & Backup Diesel Engine & 48 \\ \hline
838 & Lead-Acid & 200/1000 \\  & Battery Energy Storage System/ & 80 \\  & Photovoltaic Power & \\ \hline \hline \end{tabular}
\end{table}