# CoSimulating Communication Networks and Electrical System for Performance Evaluation in Smart Grid
## 5 Simulation Study
### Simulation Model  
**Power System:** The distribution system can be defined in OpenDSS through the DSS script. To perform simulation study of the DR application with OOCoSim, we configured IEEE 13 Node and 34 Node test feeder system as a target distribution system through the DSS scripts. On each distribution system, we placed the wind generator to simulate the impact of the dynamics of the Distributed Energy Resource (DER). However, determining the location and the output power of DER is an important issue because it highly impacts the technical benefits of distributed power system such as the power loss. There has been a lot of research to solve this problem [29; 30]. Especially, [PERSON] and [PERSON] [29] proposed an algorithm to identify the appropriate location and size (output power) of a distributed generator. At first, the algorithm calculates the _sensitivity factor_ of each bus, where \(dP_{L}/dP_{i}=(P_{L_{1}}-P_{L_{2}})/(P_{DG_{1}}-P_{DG_{2}})\). The sensitivity factor represents the change in power loss (\(P_{L1}-P_{L2}\)) of specific bus (\(P_{i}\)) when the size of distributed generation is varied from \(P_{DG1}\) to \(P_{DG2}\). After listing the most sensitive buses, the algorithm calculates the power loss for large variation of DER size in each bus. The power loss curves are almost a quadratic function [31], and the algorithm picks the bus and the size which give the minimum power loss. According to the analyses in [29], we installed the wind generator at bus 675 in 13 Node and at bus 844 in 34 Node system whose output power are 1.29 MW and 1.15 MW, respectively. Figure 5 is a graphical representation of the configured distribution system. Moreover, to consider the output diversity of the power generator, we made a probable profile for the generator in the period of 5 min according to the wind power data at Seoul, Korea, from 9 September, 09:56 to 10:00 [32] in which {4,1,0,8,2,0,4,5} m/s of wind speed are reported at each time point of {09:56,09:59,09:58,09:59,10:00}. We simply assumed that the output power of the wind generation is proportional to the wind power as \(G_{wind}(t)\propto G_{ref}\cdot wind\_power(t)\), where \(G_{wind}(t)\) represents actual output power of the wind generator and \(G_{ref}\) is the reference output power (1.29 MW for the 13 node system and 1.15 MW for the 34 node system). Figure 6 depicts the assumed output profile of the wind generator. We modified the 34 Node system by reducing each line length down to 10% since the original 34 Node system is too large to be used together with the traditional WLAN coverage. Figure 5: IEEE Node Test Feeder with local wind generator. (**a**) IEEE 13 Node Test Feeder; (**b**) IEEE 34 Node Test Feeder. Figure 6: The assumed output power of the wind generator. To verify the impact of the networking system, we employed two network systems for the distribution system: the one with a WLAN Mesh topology (Figures 7a and 8a), and the other with a combined topology of WiMAX and Ethernet backbone (Figures 7b and 8b). The network topology of each system was designed considering the practical feature of communication devices. For example, the distance between the bus 650 and the bus 632 is about 610 m, while the distance between the bus 632 and the bus 645 or the bus 633 is about 152 m, according to [33]. Since increasing the communication range for only one node could lead to the inefficient design of the wireless network, we connected the energy management system of bus 650 to the backbone network (WiMAX) or the mesh router (WLAN Mesh). Then, the APs (WLAN Mesh) or the BSs (WiMAX) are deployed to connect the wireless devices running the enenrgy management system for each bus. We modeled the network system with server/client model. The gateway energy management system acts as a server and the other energy management systems perform the role of a client. The specific configuration for each node is as follows:  
* The gateway energy management system is a wlan_server or ethernet_server node model in OPNET.