22. Edge computing


Edge computing refers to a distributed computing architecture characterised by decentralised processing power. Specifically, it enables data to be processed directly by the device that generates it or by a local computer. In this scenario, there is no longer a need to transmit large volumes of data to a remote data centre for analysis. Edge computing facilitates real-time processing of data in large quantities, as close as possible to its source, leading to reduced bandwidth usage, lower latency, and the necessary security layer for handling sensitive data. This technology is primarily prevalent in the Internet of Things (IoT) domain, where it competes with cloud computing.


Edge computing is evolving as new technologies such as artificial intelligence and machine learning bring new data analysis capabilities to the table, and emerging business models such as IoT as a service enable solution providers to deliver innovative offerings in new ways. With an average increase of 16% per year, spending on edge computing totalled $40 billion in 2022 in Europe and should reach $64 billion in 2025. Service providers, editors and manufacturers are sharpening their offers to meet the growing demand from companies.

Challenges and opportunities for DSOs


  • The enhancement of computing capabilities enables the execution of complex distributed analyses, especially in primary and secondary substations.
  • Provides flexibility to the network and minimises reaction times by enabling local decision-making.
  • Facilitates the autonomous operation of the medium (MV) and low-voltage (LV) network.
  • Addresses cybersecurity concerns.
  • Optimises data storage.


  • Equipment lifecycle.
  • Increased likelihood of failure and difficulty in settling responsibilities. This is attributed to the integration of currently independent devices, resulting from the integration of various use cases.

EDSO Considerations

  • DSOs should conduct analyses and implement demonstrators to identify relevant use cases for edge computing.
  • The technical benefits of edge computing solutions are evident for secondary substations. It is necessary to be monetised.
  • DSOs should also recognise the contribution of such solutions at primary substations and throughout the network.
  • Active participation in ongoing industry discussions is crucial for DSOs. These discussions should encompass governance and standards, including aspects such as cybersecurity, software solutions, and the definition of future standards.
  • Participation is vital to advocate for the specific requirements of DSOs.
  • DSOs need to develop a comprehensive security strategy for edge computing.

Potential use cases

  • Data concentrator. This system collects and aggregates data from various sources in the power grid, mainly smart meters, serving as a centralised point for managing and distributing information.
  • Advanced LV monitoring. Monitoring of all LV circuits in the secondary substations.
  • Power grid prediction. Load flow simulation, technical loss balance, transformer saturation, network capacity analysis, voltage mapping, and low-voltage line base balancing.
  • Asset management in secondary substations. Inventory and lifespan estimation, self-diagnosis, remote equipment reboot.
  • Power grid automatisation. Anomaly detection in LV, insulation fault detection, anomaly detection in MV, cutting, reconnection and load balancing.
  • Communication network analytics. Topology connectivity meters, fraud detection and prevention, noise detection in power-line communication (PLC) network.
  • Energy management. Local demand management, flexible generation power, distributed flexibility, integration of storage systems.
  • Physical security/access control.
  • Video analysis for visual monitoring.

Ongoing projects

  • The E4S Alliance (Edge for Smart Secondary Substation) deserves special mention. E4S works on defining a standards-based, open, interoperable, and secure architecture to enhance the automation, scalability, security, and manageability of secondary substations worldwide. Involved DSOs are i-DE, E-EDES, Enedis and UFD (more info).
  • i-DE and Iberdrola Group:
    • E4S (role: DSO) with a pending demonstration pilot during the second half of 2024.
    • VIRTGRID (role: external validator DSO).
    • IA4TES (role: promoter), testing Artificial Intelligence (AI) use cases and software applicable to the edge.
    • SEC2GRID (role: external DSO validator), testing cybersecurity in distributed environments and virtualisation of cyber use cases.
    • Virtual Data Concentrator (internal development pilot at i-DE).
    • DPP solution (2032). RFI analysis and evaluation of state-of-the-art edge computing solutions to adapt to the DSO environment.
    • MiDE4S (2021). Demonstrative piloting of Minsait solution in i-DE’s environment.
  • UFD and Naturgy Group:
    • E4S (role: DSO) with a pending demonstration pilot during the second half of 2024.
    • A field pilot for on-load tap changers (OLTC) and smart fuse integration is under definition.
  • Stedin:
    • Piloting AI on the edge with high frequency or real-time data collection (from sensors, microphones and thermal cameras) in substations primarily for asset management and prediction.
    • Piloting modular architectures on edge computers to test security risks and flexibility benefits.

Last update: 17 May 2024