## 5 Analysis of the Solution and Simulation
### Simulation Scenario
The topology under simulation is shown in Figure 10. In the interest of providing a general picture of the network performance, two potential node distributions are taken into account in the same topology: nodes deployed in the framework of an outdoor substation (cluster-tree topology and smaller separation distances between nodes) and nodes placed in electric towers along the distribution segment of the power grid (following a line topology). Nodes 1-5 are equipped with vibration sensors (which can be used to monitor for excess vibration in the electric towers and aid in determining their structural integrity) and temperature sensors to check the temperature variations in the conductors (identified as the major cause of sagging). On the contrary, nodes 6-9, deployed within the substation, (and placed in transformers, circuit breakers, feeder bays, _etc._) include temperature and acoustic sensors to detect potential partial discharges and monitor the operating temperature. To this aim, the MTS310 environmental sensor board [74] (fitted with a temperature sensor, an acoustic sensor and a dual-axis accelerometer) is simulated. Physical data (sensors readings) are acquired every 5 min (_sensing frequency_), processed, and sent if the asset is failing in simulated data bursts. Besides, every 15 min sensor readings are obligatorily sent to the central node regardless their value to have an updated record of the status of assets (_reporting frequency_). The central node processes all of this information and, if a faulty functioning is detected in any power asset, simulated commands are sent back to nodes to correct these eventualities. The results achieved with our approach are compared to a non-beacon ZigBee network where nodes 5, 8 and 9 (RFD) use duty-cycling techniques whereas the rest of them (FFD) must remain awake to route RFDs' messages. The reason why a non-beacon network has been selected instead of a beacon-enabled network is twofold: firstly, a beacon-enabled network is not a flexible and scalable solution that could be deployed in a Smart Grid environment, and therefore, _a priori_, it cannot be used in real scenarios. Lastly, although there exist two approaches for implementing a beacon-enabled network in a cluster-tree topology, namely _time division approach_ (TD) and _beacon-only period approach_ (BOP), both of them exhibit many drawbacks. The TD implementation prevents the use of broadcast messages between FFDs, which negatively affects the operation principle of the AODV protocol and excludes the creation of multi-hop routing paths. On the contrary, in the BOP approach, beacon broadcasters (FFDs) are forced to be deployed at precise locations to ensure global network synchronization [75]. These locations might have no power asset to control. Concerning the power consumption calculations, the following two considerations are taken into account. Firstly, vibration and acoustic readings take 3 s to be completed (because of sensor stabilization times) whereas the temperature can be read in just 25 ms. Secondly, the current draw (according to their corresponding datasheets and [76]) is as follows: 9.5 mA for the accelerometer and the acoustic sensor, and 7.5 mA for the temperature sensor.