5G Communications in the Energy sector

Evolution of communications in electric grids

The modernization of the Energy sector has been witnessing fundamental changes, with the information and communication technologies (ICT) playing a key role. In the last decade distributed renewable energy resources have been paving the way for the highly needed decarbonisation of the sector. With it came the inclusion of advanced management and control schemes, which provide improved monitoring and automation capability to the energy grids and the ability to support new services and functionalities. The concept of smart grid goes one-step further, relying on intelligent schemes that run on ICT infrastructure capable of coping with different operational requirements and ensuring the necessary data exchange. On one hand, it is necessary to preserve the robustness of the electric grid characterised by high levels of reliability, availability and security and, on the other hand, it is possible to add the flexibility brought by adaptable and scalable mechanisms of energy resources to deal with the dynamic nature and growth of the grid.

The digitalization process has been initiated in the transmission and distribution side, where systems like SCADA have already been used for decades in substations, to monitor and manage assets through a growing number of connected devices and systems, such as remote terminal units (RTU) and intelligent electronic devices (IED). Smart meters have been deployed to monitor the demand consumption and more recently the generation, and to support the management of the grid. They also drive the digitalization of the distribution grid with monitoring and automation features installed in secondary substations, which act as intermediary nodes of a large and complex digital system. Adding to the puzzle is the generalization of distributed renewable generation and electric vehicles, with their highly desired dual roles: as flexible loads or as potential generators.

The heterogeneity of operational requirements in the different segments of the grid and the need to exchange more data to support advanced services and functionalities (e.g., grid monitoring, energy forecasting, predictive control, enhanced grid automation) is introducing new problems that require the exploitation of diverse ICT systems. The result so far is a plethora of technologies and solutions tailored to either general or specific needs [1]. Although the harmonization among electric grid segments has been supported by industry-led standards, notably from the IEC, it is still necessary to solve cross-segment specificities that have been raised with distributed management and control strategies. These were triggered almost 20 years ago by revolutionary concepts such as the microgrid, with several reinterpretations and currently reemphasized in concepts such as cloud, fog, and edge computing. Communication architectures have evolved into more complex formulations, creating yet another challenge in dealing with different needs of connectivity and data exchange for modern grid applications, as portrayed in Figure 1.

The Internet-of-things (IoT) is being used in smart grids to integrate more devices, flattening ICT architectures, whilst coping with edge and cloud concepts. Despite this and other architectural innovations, the underlying communication technologies struggle, on their own nature, to provide capable solutions for the different requirements.

The use of privately owned ICT infrastructures has been preferred due to historical reasons and specificities of the electric system, i.e., the need to keep it isolated from other systems. The option for telecom-based technologies like 4G has been reluctantly taken in cases where other technologies are either expensive or incapable of fulfilling the requirements. Telecom services for smart grid application have been a niche, as the core business of telecom operators is not entirely aligned with the needs of utilities. Cellular technologies still introduce limitations to the exploitation of flexible business models for grid applications with an impact on costs, particularly in cases where to support specific scenarios the compensation of lost revenue comes with a non-negligible price tag. This is an opportunity for 5G to contribute to the change of the current status quo.

5G as enabler for the Energy sector

5G technologies are changing the game and assuming an important role in the Energy sector, as enablers of new services, applications, and business opportunities. Key concepts and architectural aspects [2] that distinguish 5G from earlier cellular technologies (including 4G, which 5G will progressively replace) make it suitable to support the most critical requirements of diverse technical and business use cases of the energy context.

5G New Radio technologies allow much higher data rates, with different channel sizes and flexible resource allocation modes tailored to the type of service to support; this does not preclude the use of other wireless access technologies (e.g., 4G), which may coexist during an interim period.

5G networks rely on software-based techniques, namely virtualisation of network functions (e.g., access and mobility management, authentication, policy control) that run on a general-purpose hardware platform, and on the adoption of the software-defined networking paradigm that allows dynamically reconfiguring and speeding up the packet forwarding process.

The organisation and operation of 5G networks is centred on the novel slice concept. As illustrated in Figure 2, network slicing is used to create and run multiple, self-contained logical networks on a common physical infrastructure. A slice is configured with network functions, applications and resources to meet the requirements of a specific use-case, coupled with a business purpose.

The role and importance of 5G in the Energy sector may be assessed now from different perspectives.

First, the 5G technology may be used in all segments of the electric grid and the 5G network architecture is easily integrated with the cloud computing model. A flexible and optimised development and deployment of smart grid applications is, thus, possible; for example, time-critical applications may run in edge systems, closer to the information sources, while computer intensive functions may be offloaded from end-user systems with reduced processing capability (e.g., IoT devices) to an edge or central cloud. First, the 5G technology may be used in all segments of the electric grid and the 5G network architecture is easily integrated with the cloud computing model. A flexible and optimised development and deployment of smart grid applications is, thus, possible; for example, time-critical applications may run in edge systems, closer to the information sources, while computer intensive functions may be offloaded from end-user systems with reduced processing capability (e.g., IoT devices) to an edge or central cloud.

Secondly, typical smart grid applications may be supported on standard slices already defined to address generic service categories with very different characteristics and requirements, but slice customization is possible too.

Smart metering is a case for using a massive Machine Type Communications (mMTC) slice, which is optimised to handle a large number of devices that generate low volumes of non-time-critical data. Coordination of microgrid automation systems may be mapped to an Ultra-Reliable and Low Latency Communications (URLLC) slice, which is targeted at applications that have stringent delay requirements and need very high reliability and availability. Video surveillance of critical infrastructures (e.g., primary substation) fits well into an enhanced Mobile Broadband (eMBB) slice, which is intended for (multimedia) applications that require high data rates. Using 5G drones in surveillance, planned maintenance activities or emergencies requires two types of slices: eMBB for video processing and analysis and URLLC for drone flight control.

Finally, the potential use of 5G in the Energy sector goes far beyond the current applications. As the technology becomes widely adopted and matures, more advanced use cases and business models will appear, benefiting from the assessment of experimental results and the expertise gained with the use cases of today.