The energy industry finds itself in the midst of a transformative era. In 2023 alone, a record 31 GW of solar energy capacity were installed—a 55% increase from 2022—while battery energy storage systems also saw significant growth. Legislation such as the Inflation Reduction Act (IRA) is reshaping the energy industry.
COMMENTARY
Meanwhile, petroleum and natural gas are projected to remain the most-consumed energy sources in the U.S. through 2050. In 2023, natural gas consumption reached an all-time high of 89.1 billion cubic feet per day, with the electric power sector accounting for the largest increase. U.S. energy consumption generally is expected to continue to grow through 2050 as population and economic growth outpace energy efficiency gains.
AI Has Already Changed Our World
Artificial intelligence (AI) has emerged as a crucial tool in helping those in the energy industry navigate this deeply complex transition. How exactly does AI come into play on these initiatives? For starters, AI can be extremely valuable in managing complex grids, revolutionizing grid management by enhancing planning, permitting, operations, reliability, and resilience. For instance, California’s Pacific Gas & Electric Co. (PG&E) has been utilizing machine learning to both improve the efficiency and precision of its grid inspections and mitigate wildfire risks. By employing AI, the company can analyze extensive datasets—including smart meter readings, meteorological data, incident reports, and automated alerts from wildfire cameras—to generate immediate notifications of potential failures. This proactive approach helps identify issues such as aging transformers or nascent fires before they escalate into major disasters. AI-driven solutions can also be vital in reducing greenhouse gas emissions and improving energy efficiency across various sectors, including transportation, building, industry, and agriculture. Siemens Gamesa is using a digital twin platform for scientific computing to model its offshore wind farms, which can simulate wake effects from wind turbines up to 4,000 times faster. This data optimizes wind farm layouts, increasing production while reducing loads and operating costs. Navigating supply and demand is another key way to leverage AI. For example, UK utility EDF Energy employs AI to forecast energy demand accurately, enabling more efficient grid management and allocation. This ultimately helps improve energy supply planning, reduce waste, and balance supply and demand. Today, advanced AI is forecasting renewable energy production for grid operators and enhancing resilience of smart grids. Technological innovations are accelerating power grid models for capacity and transmission studies, and optimizing planning for electric vehicle charging networks. Large language models are assisting compliance and review with federal permitting. The future possibilities are even more enticing.
Challenges Remain
While AI is already proving to be a vital tool, the adoption of any new technology is not without its challenges. For example, while the North American Electric Reliability Corp. (NERC) has emphasized the potential of AI in enhancing data analysis, planning, regulatory functions, and cybersecurity within the bulk power system, it has also committed to monitoring and managing the risks associated with AI implementation. Monitoring risks comes with increased demand loads and the need for advanced cybersecurity measures, which could result in increased regulation for utilities—in turn increasing complexity and cost of operations. Additionally, AI requires a vast amount of energy, with AI data centers consuming eight times the power of traditional data centers. If Google were to switch to a fully AI-based search model, it would increase consumption by the same amount of energy needed to power the country of Ireland. The consideration of energy consumption is likely to trigger additional regulation and subsequent updates to physical and digital assets, as well as infrastructure. Meanwhile, organizations like Microsoft, Amazon, and Google are beginning to consider novel means of powering AI datacenters, such as bringing decommissioned nuclear reactors back online. Cybersecurity risk, a lack of qualified personnel, general resistance to changing outdated infrastructure, and other technical obstacles can all get in the way of a savvy AI implementation strategy.
Capitalizing on the Opportunity
So, what can energy industry leaders do now to bolster their team’s resources with AI? Taking advantage of educational and training opportunities to boost AI literacy is a natural place to start. Experimenting with targeted internal projects is also worthwhile. After some guessing and testing, the next step is working to develop a clear strategy to begin implementing these new solutions. Once launched, closely monitor the performance and gauge how the findings or results track to initial expectations. From there, integrate whatever insights were gained and consider that the sky is the limit in terms of where energy companies can go from there. Embracing AI is not just an option but a necessity for a sustainable and efficient energy future. For those with the willingness to learn and explore its potential—especially if they have quality guidance—the sky is the limit. As the industry navigates this transformative journey, the insights and innovations presented by AI will be crucial in shaping a resilient and forward-looking energy landscape.
https://finance.yahoo.com/news/ai-energy-horizon-powering-future-105729641.html
