A Novel Methodology for the Scalability Analysis of ICT Systems for Smart Grids Based on SGAM: The InteGrid Project Approach
2. General Methodology
- Increment of the number of nodes (amount of devices)
- Increment of the frequency of information exchange (data and commands)
- Increment of the measurements taken in each sampling period, which is especially important in the case of smart meters
- The interest denotes whether the attribute shall be considered in the analysis of the scenario or not
- The impact denotes the weight of this attribute over the qualitative analysis
- Computational resources
3. Qualitative Analysis
3.1. Classification of Attributes
3.2. Architecture Characterization—Scores
3.3. Outputs of the Qualitative Analysis
- Increment of data sources due to the new number of devices (e.g., new flexibilities in the system).
- Bigger data size (higher granularity of the data) from the data sources.
- Higher frequency of information exchange (data and commands), meaning moving towards real time operation with constant updates.
- Being point-to-point communication with a physical connection interface which can be fully used.
- A calculated latency where only if a required frequency of exchange is high enough for response times (real operation for control purpose of asset steering) would require a small upgrade on the communication technologies from GPRS to 4G or upcoming 5G to fix it.
- Internal actor networks (intranets), which can be easily optimized if needed at anytime.
4. Quantitative Analysis
4.1. Overview of Simulation Tools and Related Work
- Decoupled simulations. This approach is based on simulating each par of the problem independently using a commercial or validated software. On one hand, this approach uses appropriate state-of-the-art simulations for each dimension. On the other hand, it is limited since it is difficult to relate the output of each simulation. Some examples of this approach available in the literature are , where the performance of a wireless communication architecture for energy efficiency and Distributed Generation integration is evaluated taking into account the characteristics of the underlying power infrastructure , or the evaluation of the performance of the NB-PLC technology PRIME (PoweRline Intelligent Metering Evolution) using the well-known simulator SimPRIME  in different Smart Grid scenarios, such as Advanced Metering Infrastructures [37,38,39,40,41] or Demand Response . All these studies were carried out using OMNeT++ Communication Network Simulator.
- Monolithic simulations. An straight-forward alternative to improve previous design is to build a simulation model that includes all the effects of both the telecommunication and power system’s part of the problem. Although this would provide good and more realistic results, the creation of such software will be complex and time-consuming. One specific aspect that makes this task very complex is the fact the the kind of effects that need to be modeled in each part of the problem (the telecommunication and the power systems) require a different simulation approach. Whereas the telecommunication simulations are based on event-based simulations, the power system simulations are based on the solution of transients through differential equations. The reader can refer to some monolithic simulators in the literature such as the Electric POwer and Communication syncHronizing Simulator (EPOCHS)  or the Global Event-driven CO-simulation framework (GECO) .
- Co-simulation. An alternative to previous approaches is the co-simulation. The basic idea underneath it is the use of specific simulations for each one of the problem and interconnect them using some kind of standardized solutions. This adds some more computational complexity but provides more realistic results, since one simulator is fed-back with the partial results of the other and vice versa. The Virtual Grid Integration Laboratory (VirGil)  is an example of this approach that uses Functional Mock-up Interface (FMI)  to interconnect three simulators: PowerFactory, OMNeT++ and Modelica. This project was followed-up by the CyberPhysical Co-Simulation Platform for Distributed Energy Resources in Smart Grids (CyDER) . Moreover, one additional advantage of this type of solution is the possibility of including Hardware-in-the-Loop (HiL) in the simulation, as reported in . A complete overview of other research initiatives is available in .
4.2. Considered Scenarios
- Scenario A (links 5’, 9’, 10’, 11’): The communication layer-stack in this scenario is set to DLMS/COSEM messages being transmitted over TCP/IP/GPRS.
- Scenario B (links 9 and 10): The communication layer-stack in this scenario is set to DLMS/COSEM messages being transmitted over G3-PLC.
- Scenario C: The communication layer-stack in this scenario is set to DLMS/COSEM messages being transmitted over TCP/IP/xDSL. This technology was included in the simulation as an alternative to GPRS (e.g., for link 11’). It can be also seen as a replicability and scalability analysis for links in Scenario A.
4.3. Simulation Modeling
- 300 m: 25 Mbps,
- 2 km: 16 Mbps,
- 5.2 km: 800 Kbps.
4.4. Simulation Setup
- The number of nodes in the networks. In order to model different network sizes, simulations consider 10, 100 and 1000 nodes.
- Maximum Segment Size (MSS). For the cases where TCP is part of the protocol stack, the length of the TCP segments have been set to 413 and 1600 bytes to cover a higher or lower message fragmentation.
- Channel impairments. Different channel qualities have been modeled by setting the transmission rate to different values. This models the fact that, for noisier channels, the communication protocols adapts by using a more robust communication mode and, thus, a lower transmission rate. Given this, for G3-PLC, the transmission rates have been set to , 34 and kbps, according to the standard. For xDSL, transmission rates have been set to 800 kbps, 16 Mbps and 25 Mbps. In both cases, the different values model noisier to less noisy channels.
- Frequency of message exchange. To model different applications, nodes transmit messages at the following frequencies: 10 minutes, 1 minute and 1 second, going from near-real-time to real-time.
- Percentage of link usage.
- Round-Trip Time (RTT) required for the request/response messages to be sent for all nodes in the network.
- Round-Trip Time to communicate with All nodes (RTTAll) in the network.
4.5. Simulation Results and Discussion
4.5.1. Scenario A (Links 5’, 9’, 10’, 11’)
4.5.2. Scenario B (Links 9 and 10)
4.5.3. Scenario C (Link 11’)
5. Conclusions and Future Work
Conflicts of Interest
Appendix A. Deviation Values in Simulations
|Scenario||RTTAll [s]||Usage (Up-Link) [%]||Usage (Down-Link) [%]|
|Scenario||RTTAll [s]||Usage (Up-Link) [%]||Usage (Down-Link) [%]|
|Scenario||RTTAll [s]||Usage (Up-Link) [%]||Usage (Down-Link) [%]|
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|SGAM ID||Source||Receiver||Protocol||Information Object||Frequency of|
|11’||PLC (PLC: Power Line Communication)|
concentrator at secondary substation
|DSO-network||DLMS, COSEM (DLSM, COSEM: Device Language|
Message Specification, Companion Specification
for Energy Metering respectively) (IEC 62056-5-3)
|15-min (P, Q) & (U, I) (P, Q, U, I: active power,|
reactive power, voltage, current respectively) MV/LV
(MV/LV: Medium Voltage/Low Voltage respectively)
|Once per day||DLMS||TCP/IP (TCP/IP: Transmission Control|
Protocol/Internet Protocol respectively) over GPRS
(GPRS: General Packet Radio Service)
|Possible impact into the|
scaling of the system
|Will have a great impact|
and is a constraint
|Medium impact and|
could be a constraint
|Low impact, will hardly|
become a constraint
|Interest||3—Very important||2—Important||1—Not important|
|Measures if the attribute|
shall be taken into consideration or not
|Must be included|
into the analysis
|Nice to have, but|
not fully necessary
|Attribute is not|
interesting at all
|Reliability||Autonomy (C) a|
Protocol Robustness (L) b
Protocol Reliability (C & L) c
Cyber-Security (C & L)
|Computational Resources||Storage (C)|
Processing speed (C)
Channel capacity (L)
Channel latency (L)
|Manageability||I/O Handling (C)|
Configuration effort/complexity (C & L)
Automation (C & L)
Tech. generation (C & L)
|1||Not upgradable, Lower than 1 GHz|
|2||Not upgradable, Lower than 2 GHz|
|3||Not upgradable, Lower than 5GHz|
|4||System used in the scenario under study, scalable upon manual request|
|5||System used in the scenario under study, scales automatically|
|Actor-Type||Weight—Large Customer Commercial VPP|
|SGAM ID||Source||Receiver||Application Protocol||Data Structure||Communication Technology|
|2–3||Smart Meter @ PSS—through Switch||DSO—Network (router)||DLMS, COSEM (IEC 62056-5-3)||COSEM||Fiber optics|
|4||Smart meter per MV feeder||DSO—Network (router)||DLMS, COSEM (IEC 62056-5-3)||COSEM||Fiber optics|
|5’||Smart Meter @ SSS||DSO—Network (router)||DLMS, COSEM (IEC 62056-5-3)||COSEM||TCP/IP over GPRS|
|7||Data concentrator @ SSS||DSO—Network (router)||DLMS, COSEM (IEC 62056-5-3)||COSEM||Fiber optics|
|9||Smart meter per DER (DSO)||Data concentrator @ SSS||DLMS, COSEM (IEC 62056-5-3)||COSEM||G3 PLC|
|9’||Smart meter per DER (DSO)||Data concentrator @ SSS||DLMS, COSEM (IEC 62056-5-3)||COSEM||TCP/IP over GPRS|
|10||SM per LV customer (DSO)||Data concentrator @ SSS||DLMS, COSEM (IEC 62056-5-3)||COSEM||G3 PLC|
|10’||SM per LV customer (DSO)||Data concentrator @ SSS||DLMS, COSEM (IEC 62056-5-3)||COSEM||TCP/IP over GPRS|
|11’||Data concentrator @ SSS||DSO—Network (router)||DLMS, COSEM (IEC 62056-5-3)||COSEM||TCP/IP over GPRS|
|SGAM ID||Source||Receiver||Scenario||Protocol Stack||Best Case||Worst Case||KPI|
|Link usage (%)|
|9’||Smart meter per DER|
|10’||SM per LV customer|
1 s freq.
|9||Smart meter per DER|
1 s freq.
|10||SM per LV customer|
1 s freq.
|Transmission Rates in kbps|
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Potenciano Menci, S.; Le Baut, J.; Matanza Domingo, J.; López López, G.; Cossent Arín, R.; Pio Silva, M. A Novel Methodology for the Scalability Analysis of ICT Systems for Smart Grids Based on SGAM: The InteGrid Project Approach. Energies 2020, 13, 3818. https://doi.org/10.3390/en13153818
Potenciano Menci S, Le Baut J, Matanza Domingo J, López López G, Cossent Arín R, Pio Silva M. A Novel Methodology for the Scalability Analysis of ICT Systems for Smart Grids Based on SGAM: The InteGrid Project Approach. Energies. 2020; 13(15):3818. https://doi.org/10.3390/en13153818Chicago/Turabian Style
Potenciano Menci, Sergio, Julien Le Baut, Javier Matanza Domingo, Gregorio López López, Rafael Cossent Arín, and Manuel Pio Silva. 2020. "A Novel Methodology for the Scalability Analysis of ICT Systems for Smart Grids Based on SGAM: The InteGrid Project Approach" Energies 13, no. 15: 3818. https://doi.org/10.3390/en13153818