Optimising the grid with advanced edge intelligence

Grid attention is shifting from high to medium and low voltage, a long-standing priority for Gridspertise, as highlighted in CEO Robert Denda’s unique perspective.

The European Union is progressing towards a sustainable energy future but faces challenges in transitioning to renewables. Mario Draghi’s “The Future of European Competitiveness” emphasizes faster investment in renewable energy and grid infrastructure to accelerate decarbonization, requiring efficient planning, accelerated permitting, financing, and innovating grid assets and processes at the EU and Member State levels.

To meet 2050 decarbonisation targets, the EU must double the annual installation rate of renewables compared to the average of the past five years, and it is estimated that by 2030 up to 70% of new renewable generation will be integrated at the distribution grid level. Moreover, to reach the decarbonisation targets, electricity needs to cover 60% of European final consumption, up from 22% in 2022.

The rise in distributed energy resources (DERs), electricity demand and the need to accommodate new charging loads from electrification of heating and transportation add complexity to the distribution grid, shifting attention from high to medium and low voltage (MV/LV) grids and making their digitalisation a priority.

What advancements have been made in medium and low voltage grid digitalisation – and what challenges remain?

Digitalisation is crucial to deploying clean energy and creating a future-proof, reliable, resilient, and safe grid at the necessary pace. In addition to addressing the pressing challenges in the power sector, there is a significant opportunity to fully leverage digital technologies. These ready-to-deploy solutions can provide immediate value, even as we contend with the long lead-times associated with traditional components like transformers and power lines. By anticipating and integrating digital advancements, we can enhance network resilience and performance more swiftly and efficiently, ensuring a more robust and adaptable energy infrastructure.

First-generation smart meters, sensors, data analysis and control have made the grid more responsive and efficient. But with this legacy technology, utilities risk being overwhelmed, as traditional digitalisation offers centralised management but struggles with the increasingly vast data from electrification and distributed energy resources growth.

Centralised systems face high latency, scalability issues, single points of failure due to automation algorithms failing in isolating an optimal portion of network in case of lack of communication, and data breaches, especially with rising cyberattacks on Europe’s utility sector.

Legacy systems rely on outdated hardware and software, increasing cyber risks and endangering grid reliability. Additionally, they present siloed components, need frequent upgrades, and rely on close to phase-out technologies like 2G and 3G, requiring significant hardware upgrades.

The traditional approach leveraging on centralised intelligence is no longer effective or sustainable. New technologies are needed to complete the distribution networks’ transition into resilient decentralised grids and they are already available.

What are the solutions to the risks of traditional electricity system digitalisation?

Edge intelligence is crucial for decentralised grids, allowing real-time monitoring, control and decision-making, optimising local energy distribution, and ensuring efficient use of renewable resources while scaling and integrating DERs and electric vehicle charging loads.

Advanced edge computing devices enable local operations to continue independently during communication interruptions, enhance security by reducing the transmission of sensitive data, and ease the load on central infrastructure. They are natively cyber-secured and, due to distributed edge architecture, increase resilience to communication faults.

These advanced solutions, such as Gridspertise’s Quantum Edge^® device – QEd, can work as an open platform, multi-protocol and multi-technology, integrating different functions and external smart devices through the same hardware. Different hardware components can be virtualised in an all-in-one solution with the possibility to run applications on the edge.

Edge computing devices are also future-proof, supporting state of the art technologies like 4G, LTE and fibre communication protocols, and are capable of adapting to new grid requirements through installation of new virtual apps.

At Gridspertise we have extensive field-proven expertise in edge computing. Our flagship projects in Europe, Latam, India and the US illustrate how edge intelligence can significantly improve grid operational efficiency, provide enhanced observability and contribute to improvements in SAIDI, SAIFI, quality of voltage and smart metering KPIs.

What future innovations does Gridspertise plan to implement to enhance electricity grid management?

Our differentiation advantage is our expertise in the MV/LV distribution grid, leveraging our knowledge in both metering and grid technologies. We are a one-stop shop for distribution system operators, offering end-to-end cloud-edge solutions from the secondary substations to the meters.

Integrating hardware, data, intelligence and exploiting a cloud-edge continuum architecture will help us run sophisticated applications and maximise the value of artificial intelligence (AI) in solving the challenges of the complex MV/LV infrastructure.

Among the main use cases, AI can analyse grid topology to adjust and reconfigure power flow without latency and can process historical data and real-time information to predict and balance supply and demand.

AI can perform power flow analysis, hosting capacity, and new connections viability calculations to support the integration of renewables and EV in the MV/ LV network.

Through the analysis of sensor data from grid components, AI enables proactive predictive maintenance, preventing outages.

By assessing patterns in energy usage and identifying unusual deviations, AI can detect anomalies such as fraudulent activities like meter tampering or energy theft.

Finally, AI can support utilities in strengthening the performance of their workforce. By leveraging AI, they can optimise grid operations and also upskill their personnel, bridging the skill gap.

Transitioning to a service and data-driven company, we can gain a deeper understanding of our customers’ infrastructure, behaviour and needs to develop increasingly sophisticated applications of AI. Our primary goal is to solve our customers’ problems while keeping innovation at the core of what we do.

About Robert Denda

Robert Denda, CEO of Gridspertise, has a rich background in digital grid technologies and smart metering. He previously led innovation at Enel Grids and holds a PhD from the University of Mannheim. Under his leadership, Gridspertise focuses on advancing grid digitalisation and integrating edge computing solutions to enhance grid efficiency and reliability.

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About Gridspertise

Gridspertise offers grid intelligent devices, end-to-end cloud-edge platform solutions and services to accelerate the digital transformation of electricity distribution grids. Its portfolio easily integrates with distribution system operators’ existing infrastructure, combining intelligent and automated grid devices with ready-to-use modular applications running at central level and on the edge.