# Communication Performance Assessment for Advanced Metering Infrastructure
## 4 Simulation and Experimental Results
### Field Measurements and Communication Performance Assessment  
An actual small-scale PLC-based AMI as illustrated in Figure 7 is used to demonstrate the validity of the proposed CPI. For convenient observation, Figure 7 is redrawn as Figure 15 and the meters are renumbered and listed in Table 4. From Figure 15 and Table 4, it can be seen that there are 53 m and the DCU is used to collect energy usage data from these meters to the meter data management system. Smart meters \(M_{3}\), \(M_{7}\), \(M_{24}\), \(M_{27}\), \(M_{31}\), and \(M_{45}\) act like the routers and transmit the meter data  
Figure 14: Number of Communication Paths Used for the Six-Meter Case after Communication Paths Changed. Figure 12: Number of Communication Paths Used for the Six-Meter Case. Figure 13: CPIs for the Six-Meter Case after Communication Path Changed. received from other smart meters to DCU. Table 5 shows the field communication measurements of smart meter \(M_{1}\) used in the proposed CPI calculation. From Table 5, it can be observed that the reading success rates are between 28.13% and 100% with average and standard deviation of 89.15% and 16.74%, respectively. The reading success rate can be considered as an indicator of communication network stability. The response times are between 148.6 ms and 620 ms, with an average and standard deviation of 331.72 ms and 114.63 ms, respectively. The membership function of response time is designed in the range of 200 ms to 600 ms and is shown in Figure 16 from the field measurements. Figures 17 and 18 illustrates the calculated CPIs and calculated average CPIs for Day 1 and from Days 1 to 31, respectively. The average and standard deviation of meter CPIs from Days 1 to 31 are also listed in Table 6. Based on the calculated CPIs, the communication performance of each meter can be supervised. For example, Figure 19 shows the CPIs and 5-day average CPIs of smart meter \(M_{1}\). From Figure 19, it can be observed that \(M_{1}\) has worse CPIs in Days 14, 15, 19, 22, 23 and 24. The possible causes can be further investigated. Obviously, from Figures 17-19 and Table 6 the communication performance and stability of smart meter \(M_{1}\) can be effectively and efficiently assessed and supervised. Since the field communication measurements used in the proposed CPI can be effortlessly acquired from smart meters, the proposed communication performance assessment has great potential to be integrated into a large-scale AMI to support its operation. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Meter** & **ID** & **Meter** & **ID** & **Meter** & **ID** & **Meter** & **ID** \\ \hline
1 & 3c4b9 & 15 & 3c4 ab & 29 & 3c4 ba & 43 & 3c4c9 \\
2 & 3c4b7 & 16 & 3c4a2 & 30 & 3c493 & 44 & 3c4c8 \\
3 & 3c4c0 & 17 & 3c487 & 31 & 3c4c1 & 45 & 3c4c7 \\
4 & 3c4b4 & 18 & 3c484 & 32 & 3c4 bf & 46 & 3c4c3 \\
5 & 3c4b6 & 19 & 3c486 & 33 & 3c4 be & 47 & 3c4c5 \\
6 & 3c4b5 & 20 & 3c485 & 34 & 3c4b1 & 48 & 3c4 cc \\
7 & 3c4b3 & 21 & 3c483 & 35 & 3c4 aa & 49 & 3c4 bb \\
8 & 3c4b0 & 22 & 3c482 & 36 & 3c4 ac & 50 & 3c4c2 \\
9 & 3c4 af & 23 & 3c47f & 37 & 3c4a4 & 51 & 3c4 bc \\
10 & 3c4 ad & 24 & 3c4 cf & 38 & 3c4a5 & 52 & 3c4 bd \\
11 & 3c4 ae & 25 & 3c480 & 39 & 3c4a6 & 53 & 3c4c6 \\
12 & 3c4a9 & 26 & 3c481 & 40 & 3c4 ce & - & - \\
13 & 3c4a8 & 27 & 3c4c4 & 41 & 3c4 cb & - & - \\
14 & 3c4a3 & 28 & 3c4b2 & 42 & 3c4 ca & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Meter Number for the Actual Small-Scale PLC-based AMI. Figure 16: Membership Function of Response Time for Actual Small-Scale PLC-based AMI.