Energy Expansion: A More Realistic Narrative

Alvaro Rozo is Chief Product Officer of Arcus Power Corp.

I remember when our CEO, Daniel Erhardt, told me there is no energy transition. He often says there is an energy expansion. I think that's the right terminology to use because, in reality, there is a requirement for the coexistence of many different energy technologies moving forward. And global energy use is projected to continue growing. But what will that look like?

Germany leaned heavily into renewables with notable risk to its position as a manufacturing leader. It achieved great results over the last decade, with both fossil fuel use and total emissions down around 24%, but the resulting dependency on other regions is causing persistent economic underperformance. On the other hand, dependency on large power plants or solar fields can also be risky in areas where you see storms or tornadoes happening on a regular basis, like we saw in the impacts of Hurricane Milton.

For those reasons and many more, which I’ll explain in this article, I believe the global power expansion demands a balance between energy innovation and reliability. As countries navigate the challenges of integrating diverse technologies into their grids, I also think humans are needed more than ever as key decision makers—not AI systems alone. Here is why.

The Role Of AI In Enabling Smarter Energy Systems

In countries where the AI agenda has been pushed, these large models are driving energy consumption and energy requirements across the board. And we’re also seeing a push to digitize almost everything, which requires a lot of energy that can’t be fully calculated yet. Still, Amazon, Google and Microsoft are investing in nuclear technologies because that's where they see the future for them to deliver the energy that they require for EVs, data centers, LLMs and digital currencies among other trends.

Breaking down high-energy AI into smaller and optimal processes at every phase—experimentation, testing, backtesting and operationalization—allows companies and data centers to implement better strategies to balance performance, costs and carbon footprint associated with AI. As ESG and other regulatory frameworks start to become more stringent, every part of the AI value chain will need to measure and report their energy consumption and emissions profiles. As AI becomes a critical component of every business operation, adjusting AI-driven applications based on their specific demands and conditions will be key to the success of energy expansion and scaling distributed energy resource management and data centers.

The Need For Resiliency In Energy Infrastructure

The power market is moving toward a more intelligent energy grid where devices can make decisions in an autonomous manner. Increasing environmental catastrophes are projected to increase the number of outage events per person in some counties by over 50% in the next decade according to recent research. These events will disconnect portions of grids, but distributed energy resources can help mitigate the impact it has on our lives and supply chains.

By working with distributed energy resources, companies have much greater flexibility and control in distribution and even transmission networks. Localized energy production and consumption, while seemingly difficult to transition towards, reduces dependency on centralized grids and makes the power supply more reliable under changing conditions. Strategically locating battery storage facilities or generators in locations where you know there’s low risk from storms or tornadoes are great ways to ensure your power sources are resilient to new environmental risks. Smaller-sized data centers deployed as close as possible to operations offer new opportunities for resiliency in an expanding energy grid.

I also see a growing need for more localized resiliency measures on the part of energy producers to combat the rise in storm activities. Some 3.4 million homes and businesses in Florida were recently left without power in the wake of Hurricane Milton alone.

Florida Power & Light (FPL) faced the most severe outages, leaving 1.2 million customers without power. Viral stories showed the impact on one of their solar fields, bringing into question the resilience of clean energy technology. But only 0.05% of FPL’s roughly 16 million solar panels were affected by the hurricanes, and the one impacted site regained power in four days.

The Democratization And Smart Use Of Energy Data

At the core of resiliency planning is the need for democratized energy data. Companies and governments alike should have information about every relevant part of the energy grid, and it should be presented in a way that they can actually take advantage of that information. Then, data centers, energy producers and local communities can use public and proprietary information to make decisions tailored to their individual operating environment.

The typical challenge with forecasts has always been how to actually utilize that forecast. A one-size-fits-all approach just doesn’t provide a competitive advantage. AI shall augment the capabilities or the skills people have by providing insights and relevant information that they can utilize to make smarter, faster decisions. It is imperative to consider that we are dealing with critical infrastructure, technology can fail so people need to be fully trained to step in to ensure safety and continuity of operations. As energy leaders, rather than forcing companies or our own employees to adopt AI systems to understand energy data, we should help them adapt by combining legacy expertise with modern technologies. This sort of cross-pollination between knowledgeable employees and new adopters creates a better balance of skills and promotes knowledge transfer, leading to more modern, safe, reliable and sustainable operations.

Practical Takeaways For The Workforce

To meet growing energy demands, energy leaders need to embrace collaboration between humans, AI and data systems. AI-driven intelligence can optimize energy use today, but it must be integrated with human expertise for maximum impact. At the end of the day, grids connect people with energy. The ability to scale operations while maintaining safety and sustainability will define future success. Decentralization introduces great opportunities for planning and coordinating capital projects and investments, for planning asset participation and their operations to contribute to the grid towards more resiliency. We’re heading toward a future where every part of the grid, from production to consumption, needs to be more interconnected and adaptive.

Energy leaders should prioritize strategies that balance traditional and renewable energy sources, integrate AI responsibly and invest in resilient systems that address both local and global challenges. By focusing on sustainability and collaboration, we can drive the energy expansion forward without compromising stability.

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