The Race Has Begun: How AI is Being Used for Energy
In April 2024, the U.S. Department of Energy’s Office of Critical and Emerging Technologies released its AI for Energy report, highlighting a significant shift in how artificial intelligence (AI) is increasingly gaining momentum within the energy industry. This sector, historically cautious about adopting new technologies, is now at a pivotal moment where AI can redefine how things are done, paving the way for the future of energy. The report underlines the trends, challenges, and opportunities that AI presents to an industry that has long relied on physics-based models to design, operate, and manage the largest machine on the planet: the electric grid.
For more than a century, the power industry has been built on a foundation of physics. The grid has been meticulously designed to best-ensure stability, reliability, and predictability. Unlike some sectors (which may be non-regulated) that rapidly adopt technological innovations, the energy sector is enthusiastic but cautious – primarily due to the high stakes (e.g., safety) and regulations involved. Any disruption or failure in the grid can have far-reaching consequences, affecting all industries and populations dependent on a stable power supply.
Opportunities and Challenges
While we need to be careful when applying new technology, the reward of innovation is vast opportunity. AI has the potential to revolutionize various aspects of energy generation, distribution, transmission, and consumption. It can enhance forecasting capabilities, improve grid operations, and enhance energy efficiency. For example, AI-driven models can predict energy demand with greater accuracy, allowing for better resource allocation and minimizing waste.
On the other hand, the integration of AI also introduces new challenges and risks. As AI systems become more intertwined with the grid, the potential for cyberattacks increases. Ensuring cybersecurity hence becomes critical. Additionally, the complexity of AI mixed with the industry’s reliance on traditional physics-based models can create tension between innovation and caution.
An Industry Shift
We are collectively witnessing a shift from incremental to exponential changes facing the energy industry – and it’s no longer “business as usual”. AI is accelerating the pace of innovation, and we need to find new ways of doing things. Embracing AI could lead to significant improvements in grid management and sustainability objectives – but we also know that rapid changes requite rigorous strategies to manage the transition and mitigate potential disruptions.
1. Predictive/prescriptive maintenance: AI can make us more proactive vs. reactive with predictive analytics.
2. Forecasting: AI can enhance planning and forecasting, especially as demand grows to levels never seen before. More accurate predictions can aid in balancing supply and demand, reducing costs and preventing blackouts.
3. Cybersecurity: This is an interesting one. While on one hand, AI opens up major risk with respect to cybersecurity, it can also bolster cybersecurity measures by identifying and responding to threats quickly. Machine learning algorithms can detect anomalies and potential breaches, allowing operators to be proactive.
4. Zonal Autonomous Control: AI can enable Zonal Autonomous Control and help manage specific sections of the grid.
Despite promise, there is a requisite for a balanced approach. The energy industry must navigate the integration of AI with caution, ensuring that new technologies do not compromise the stability of the grid. Collaboration is crucial to developing solutions that leverage AI’s strengths while simultaneously addressing its limitations.
Furthermore, regulatory frameworks and industry standards need to keep pace with technological advancements. Guidelines need to be in place to promote innovation while also ensuring safety and security. And while we’ve been using forms of AI for a while, advances in AI technology are enabling advances everywhere else. Realizing the potential of AI requires careful planning, robust cybersecurity measures, and a willingness to embrace change while safeguarding a grid that’s been built on a history of expertise.