How real-time data is reinventing the grid to power Europe’s future

Europe's electricity grid is undergoing a fundamental rewiring. 

Once defined by large power stations and one-way flows of energy, we’re seeing the system becoming increasingly decentralized and dynamic. Wind farms and solar panels are reshaping how electricity is generated, while millions of cars, homes and businesses are becoming miniature power stations in their own right.

This transition brings new complexity. Supply and demand can now fluctuate by the second, driven by weather, usage patterns, and local generation. To keep the system stable, operators are turning to something increasingly vital: real-time data.

A changing energy mix and flow demands real-time coordination

Throughout my career I’ve had a strong focus on the utilities industry, and one of the (many) reasons I joined Confluent was seeing, first-hand, how difficult it was to manage rapidly growing volumes of energy data using traditional systems and processes. As more renewable energies came online, so did the complexity and gaps in visibility.

Wind and solar provided 30% of the EU’s electricity in the first half of 2024, overtaking fossil fuels for the first time. It’s a major milestone that signals positive progress toward climate targets. But it also presents a major technical challenge.

Renewable energy is highly variable. And with thousands of decentralized sources feeding power into the system and pushing it back out again, operators are managing not just more volatility but a shift to bi-directional flow, creating new complications around voltage control, protection systems, regulation and forecasting.

The reality? Relying on outdated reports or batch updates is no longer viable. We need a real-time view of what’s happening across the grid: where energy is coming from, where it’s going, and how to keep everything balanced in real-time.

That’s where data streaming plays a critical role. By moving data the moment it’s produced, streaming infrastructure powers forecasting tools, flags imbalances before they escalate, and enables automated responses that help stabilise the grid — no matter which way the energy is flowing.

Real-time systems in action

Energy organizations across Europe and beyond are already putting this into practice. It was fascinating to hear from Dr Dora Simroth, Head of Data and AI Engineering at E.ON Digital Technology, explain how real-time streaming infrastructure is helping to power the company’s green energy transition at Current 2024. By analyzing real-time data from millions of devices — including smart meters, solar panels and low-voltage grids — E.ON’s AI models can predict fluctuations in renewable output to optimize how it buys and sells energy.

Other operators are adopting similar approaches. Headquartered in Germany, Uniper is also working with Apache Kafka and Confluent to power a real-time integration platform that supports everything from algorithmic trading to energy dispatch. The platform enables agile and resilient operations across Uniper’s business, supporting its broader mission to achieve carbon neutrality by 2040.

It’s also fantastic to see how emerging ‘energy communities’ are taking advantage of data streaming to shift the model from top-down renewable investment to local, citizen-led action. Developed around shared ‘solar circles’, residents can generate and share solar power using real-time data to manage generation, storage, and demand. It’s a model that puts power — quite literally — in the hands of communities.

Growing use cases for data streaming

The use of real-time data streaming is reshaping both how utilities operate and how people interact with the energy system.

Electric vehicles (EVs) are an interesting illustration of this. Once seen as pure consumers of electricity threatening to strain the grid, they’re becoming part of the grid itself, increasingly able to supply power back through vehicle-to-grid technology.

In this sense, the millions of EVs driving around represent an untapped mobile and distributed energy resource. But managing unpredictable charging and usage patterns means knowing when, where and at what capacity vehicles are connected. With real-time streaming infrastructure, EVs can respond to demand signals, soak up excess renewable generation or feed energy back into the system when needed.

Data streaming is also enabling greater flexibility in how energy is used at home and work. Households and businesses can now adjust consumption in response to real-time signals from the grid. During periods of oversupply, for example, smart appliances or battery systems can absorb excess power automatically, which helps stabilise the system without manual intervention.By leveraging smart home connectivity and influencing consumer behaviour, these distributed actions can be coordinated, effectively turning a neighbourhood or even a city into a virtual power plant.

For energy companies, real-time data is helping to improve the customer experience, too. It allows for faster identification of billing errors, more accurate usage tracking, and the introduction of dynamic pricing based on demand. What was once delayed or reactive is now immediate, transparent, and increasingly automated.

What this means for the energy sector

From what I’ve been seeing in the sector, the ability to stream data in real-time is becoming just as critical as the physical infrastructure we rely on. It’s what supports faster decisions, smarter maintenance, and more agile operations. Organizations with real-time data capabilities are better positioned to integrate renewables, meet regulatory targets, and offer new services.

Data streaming doesn’t eliminate the complexity or volatility of energy systems, but it does offer something the old ways lacked: visibility and speed. Now more than ever, that matters. The shift to data-driven energy marks a vital move from static infrastructure to dynamic systems — the foundation of building a grid that can keep pace with change and, ultimately, keep the lights on.