On April 15, I will be speaking at EY Renewable Energy Day about grid congestion. The topic is often framed as an infrastructure problem. That’s true. But it’s not the full story.
What we see in practice is something different. Electricity networks are designed for peak demand. Those peaks do occur, but only for a small part of the time. Yet we operate the grid as if those peaks are the norm.
At the same time:
– decisions are made with limited predictive insight
– flexibility in the system remains underutilized
– available capacity is not actively managed
As a result, we create scarcity that doesn’t always need to exist. In many regions, companies cannot connect, expand or electrify. That is real. But outside peak moments, a significant part of the grid remains unused. That gap is where the opportunity sits. Not by replacing infrastructure, but by improving how we use what is already there.
This is where IT becomes critical
Improving grid utilization requires more than planning or policy. It requires systems.
Systems that:
- predict actual grid load based on data
- provide real-time insight into available capacity
- actively steer flexible assets such as EV chargers, batteries and solar
At Utilus, this is what we build. We develop and integrate the systems that make this possible. From probabilistic forecasting to real-time control, applied within existing environments.
What we see in practice
In our experiments, we see capacity gains of around 20%. That is not theoretical. It is the result of better forecasting and more targeted control. Grid expansion takes time. Permits, investments and execution can take years. In the meantime, pressure on the grid continues to increase. Better utilization provides additional room in the short term.
One of the main barriers is not technology. It is execution. Many initiatives remain conceptual. What is often missing is a clear path to implementation. In practice, this can move faster than expected.
With the right setup, you can:
- test predictive models in real environments
- apply controlled flexibility in a limited scope
- validate impact within weeks
This is what I will go deeper into during the session.
EY Renewable Energy Day
At EY Renewable Energy Day, I will share how this works in practice:
- how probabilistic models improve forecasting
- how digital control can be applied in a controlled and safe way
- what it takes to move from idea to pilot in weeks, not years
If you are working on congestion challenges, I would be interested to compare notes.