Content for  TR 22.867  Word version:  18.2.0

In the power grid, there are devices deployed to measure physical quantities from the grid, such quantities are e.g. electrical quantities such as amplitudes of voltage and current, phase, frequency or rate of change of frequency (ROCOF). One device that can provide such measurements is called a Phasor Measurement Unit (PMU). This particular device provides the above-mentioned values synchronized to a global time clock derived, for example from GPS. Such synchronized values can be used as an input to power distribution grid services, such as state estimation service [61]. Another possible service that relies on measurements of voltage, current and phase is a voltage control service [62]. As PMUs are very expensive devices, they are placed only at key points of interest. However, it is possible to use cheaper field devices that collect sampled measurement data and then process them in the edge cloud hosted PMU software, virtualizing the processing functionality of a traditional PMU, thus enabling the concept of the edgePMU [63]. Due to the lower processing requirements of the field devices, their cost is reduced, and they can also be deployed in the distribution grid providing power system operators with a more precise knowledge of the state of their grids. The edgePMU concept separates the data acquisition from the data processing by exploiting the computational capabilities offered by distributed 5G edge clouds. The edgePMU, with its modular approach, tackles the growing need for low-cost measurement devices in distribution networks from a new perspective. It utilizes the scalability of cloud infrastructure and decreases the specialization needed in the data acquisition device, by providing flexible cloud solutions for different data use cases. Furthermore, the overall deployment is simplified from a communication point of view since there is no need for special communications cabling and a network infrastructure managed by distribution grid operators. This approach simplifies the adoption of PMUs in distribution networks by helping distribution grid operators gradually deploy their measurement architectures. In fact, the cloud-based approach offers great flexibility in the development of monitoring and automation functionalities, by gradually stacking services and processing modules. It also provides scalability opportunities, thanks to the cloud technology-based computational infrastructure. The increased computational power offered by 5G edge cloud compared to that of low-cost single board computers enables more computationally challenging algorithms to be deployed. Here are the key features of the edgePMU concept [63]:

• High rate raw data transmission between the data acquisition unit and the edge cloud using 5G wireless connectivity
• The ability to deploy services or other applications on edge cloud infrastructure instead of having to deploy them in a traditional PMU with its high processing power
• A single field device can be used as a data acquisition unit for different services hosted in the edge cloud
• Services can be deployed, modified and upgraded on demand without the need to physically visit the sites
• The cloud-based software is not limited to only providing phasor measurements, but could also be used to calculate other metrics for power distribution grid services

Coverage by 5G communications networks of regions in which measurement devices and edge cloud are to be located is required. The voltage or current measurement sensors and their associated secure data acquisition units have to be deployed in the power grid. The secure data acquisition unit is connected wirelessly by the 5G network to the edge cloud hosted services. The service of phasor calculation is deployed in the edge cloud infrastructure.

• The data acquisition unit is collecting data, such as voltage and current values, from the power grid.
• This data is then sent via secure 5G communication to the relevant service hosted on the edge cloud.
• After the data has been collected in the edge cloud, the service processes the data. A small buffer is needed for post-processing with the service hosted on the edge cloud.
• In the case of the phasor calculation service, the estimated phasors can be forwarded to further applications or actors, either hosted by the edge cloud or external to it.

The relevant power distribution grid service is successfully deployed in the edge cloud and running smoothly. The voltage or current measurements are collected by the data acquisition units and transmitted to the service hosted on the edge cloud. The service deployed in the edge cloud provides upstream services, such as state estimation or voltage control, with the input data they need. The resulting service output data, hosted on the edge cloud, is stored permanently or forwarded to upstream services.

Existing LTE wireless connectivity, if configured to provide the required latency, could support the transmission of field device measurement data to services hosted on clouds hosted on distribution system operator owned servers. Latency:

None.

The Load Prediction (LP) and Generation Prediction (GP) service [52] aim at forecasting the future values of power consumption and injection, respectively, in order to give to the Distribution System Operator (DSO) the awareness on how the grid operating conditions are expected to evolve in the future. This service works by processing the historical data on the power consumption/injection of the customer, generator, or substation under analysis, and possibly taking into account other information that is likely to affect the power levels (e.g. like weather conditions, temperature, etc.). The forecast given by the LP and GP can refer to different time horizons and can have a different time resolution, according to the requirements of the DSOs. As an example, day ahead forecasts (for example with a time resolution of 15 minutes) can be generated in order to predict possible contingencies and, in case, to be prepared to take adequate countermeasures. Day ahead forecasts could be refined by shorter-term forecasts, e.g. a forecast referred to the next hour, which in general could be more reliable since it can be based on more recent information on the grid status. This could be, for example, a solution to apply preventive control schemes aimed at minimizing the risk of problems in the grid. On the other side, longer term forecasts (e.g. on a seasonal or yearly basis) are also possible and they can support DSOs in planning, and in supporting strategical decisions on managing and reinforcing the grid.

Power meters are available at the customer (or substation) site where the forecast is required. The State Estimation service (see clause 5.20 "Use case of power distribution grid state estimation" above) is deployed and active in the power distribution grid. Output of the State Estimation service can be used by the LP and GP service.

The future values of power consumption and injection are forecasted. DSO is aware of how the grid operating conditions are expected to evolve in the future, e.g., to predict possible contingencies. Longer term forecasts can support DSO in planning, and in supporting strategical decisions on managing and reinforcing the grid.

Data transmission is based on the uplink direction only, when using historic values for load and power generated. Load and generation prediction service does not take data from the field, but only the data stored in the database. Of course, the data stored in the database arrived at some point from the field. Table 5.24.5-1 shows communications requirements for the LP/GP service.

None.