Engineering the Grid for the Decade of Demand

We have entered what I like to call the “demand decade” – a period when electricity demand will grow faster than at any other time in recent memory. Electrified transport, the rise of data centers and artificial intelligence (AI), industrial decarbonization, and population growth are all converging to reshape how we generate and consume energy.

I’ve spoken about this inflection point at the recent Reuters Global Energy Transition event in New York City and again during a live webinar because I believe we’re facing both a challenge and an extraordinary opportunity. The challenge is simple: the grid, as it stands today, wasn’t designed for what’s coming. The opportunity hence lies in how we respond – by building systems that are not only larger, but secure, faster, and more resilient.

A Less Forgiving Grid
The energy transition has made the grid less forgiving. As renewables replace conventional generation, we lose the stabilizing inertia that large rotating machines once provided. With lower inertia, voltage and frequency can swing more rapidly and what used to unfold in minutes now happens in milliseconds.

This calls for a fundamental rethinking of how we design and operate our networks. Stability can no longer rely solely on mass and momentum, but rather on flexibility, near real-time intelligence, and the ability to act almost instantaneously.

AI, edge computing, and digital twin technology are helping us move from reactive control to predictive systems. They give operators the visibility to anticipate disturbances before they cascade. It’s not a theoretical ideal anymore – it’s happening now, in utilities that have begun embedding digital intelligence at every layer of the grid.

From Centralized Power to Distributed Intelligence
Two key forces are converging: rising demand and the decentralization of power generation. This means we need to shift from a hierarchal grid to a distributed one. Power will increasingly flow in two directions, and decisions need to be made closer to where data and events originate.

This is where digital substations become essential. They are no longer just physical assets, but adaptive digital nodes that are reconfigurable, software-defined, and capable of analyzing and acting locally. By embedding sensors, analytics, and edge control, substations can evolve from silent transfer points to active participants in maintaining balance and reliability.

Modeling and Managing Risk
Some recent global outages have shown just how quickly a local fault can cascade. To manage this new level of complexity, it’s important to move from static contingency analysis to dynamic modeling.

Through digital twins and near real-time simulation, operators can continuously stress-test their systems under real conditions. Combined with AI and high-resolution sensing, these tools enable a much faster, automated response. Our Zonal Autonomous Control (ZAC) technology embodies this principle, allowing parts of the grid to operate semi-autonomously while remaining harmonized with central control functions.

Breaking Down Data Silos
AI’s greatest limitation today is not the algorithm – it’s actually the data. Much of the information we need remains siloed at the edge or lost before it can be used. In my estimate, the next breakthrough will come from data fusion, combining simulations with AI to produce hybrid models that are more accurate and explainable.

Edge commuting will make this possible: by processing data where it’s generated, it’ll reduce latency, preserve context, and unlock predictive capabilities at scale. And this, well this is the key to a grid that learns as it operates.

Modernization Without Reinvention
Many utilities tell me they feel trapped between urgent modernization needs and the realities of aging infrastructure or regulatory inertia. My advice is: don’t wait for a full reset. Build evolutionarily.

Digital solutions like asset performance management and device management can be layered onto existing grid units. These tools extend equipment life, improve performance, and help direct capital to the highest-impact upgrades.

I often point to the examples of Transelec in Chile, which supplies electricity to more than 96% of the country’s population, and Tohoku in Japan - the largest APM Enterprise solution with 20M assets. By adopting GE Vernova’s GridBeats™ portfolio, specifically GridBeats™ Asset Performance Management (APM), they gathered asset-condition data, assessed risk proactively, planned maintenance effectively, and integrated with other IT systems. The result included fewer unexpected outages and higher network availability and the highest impact of their capital investment and maintenance focus. This showcases resilience in action, with data and foresight working hand in hand.

However, equally important is collaboration. Innovation that brings together utilities, regulators, and technology partners can accelerate pilots and provide evidence-based approaches. Because modernization doesn’t have to be disruptive. It can be deliberate, measurable, and fast.

As data centers, industrial players, and communities deploy their own generation and storage, grid operators are evolving into the role of system orchestrators. Their job is to integrate diverse resources (both centralized and distributed) while ensuring fairness, affordability, security, and reliability.

The Vision for a Resilient Grid
At the end of the day, a truly resilient grid is adaptive, intelligent, and collaborative. It blends technology with teamwork. It senses, predicts, and restores. And it evolves continuously to meet the changing landscape.

That spirit of collaboration is at the core of our mission. GE Vernova’s recent five-year, $50 million partnership with MIT is part of that commitment – advancing innovation in electrification and driving the energy transition while developing the next generation of energy leaders.