According to market researchers at Gartner1, “Utilities are faced with unprecedented challenges.” While international conflict, economic uncertainty and climate change are affecting businesses of all kinds, energy companies and utilities are also dealing with aging infrastructure, constant cyberattacks, increased regulation and rising customer expectations.
To overcome these challenges, energy companies are increasingly turning to artificial intelligence (AI), particularly generative AI large language models (LLM). ResearchandMarkets1 estimates that the energy and power market spent 3.103 billion USD on AI in 2021. And by 2028, the AI spend is likely to more than quadruple to 14.257 billion USD.
John Villali, research director for IDC Energy Insights2, explains: “Operational segments across the utility value chain have established use cases that have proven to be beneficial to utilities. Whether it is in generation, transmission, or distribution, the use cases and deployment of AI are on the rise in operational areas of the industry with expectations to bring utilities positive results.”
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So, what exactly are those use cases? Here’s how generative AI and AI are helping utilities address some of their most difficult challenges:
1. Overcoming a lack of resilience
Fires. Floods. Hurricanes. Blizzards. Heat waves. It seems like every other day brings a new natural disaster, and as climate change intensifies, the pace is likely to increase. Unfortunately, utilities must cope with these emergencies with outdated infrastructure. A recent report from CNBC3 noted, “Most of the U.S. electric grid was built in the 1960s and 1970s. Today, over 70% of the U.S. electricity grid is more than 25 years old, and that aging system is vulnerable to increasingly intense storms.” How can AI and generative AI help? First, AI is improving weather models so that utilities can have a better idea of where disaster might strike. AI also forecasts demand so that energy companies can plan their modernization and expansion efforts. In addition, companies use AI for proactive grid management and predictive maintenance that helps prevent outages. As a result, utilities can improve uptime for their customers while optimizing operations to keep costs low.
2. Achieving regulatory compliance
Many governments are responding to climate change by passing new laws aimed at reducing carbon emissions. In addition, utilities must comply with regulations that cover a wide variety of other areas:
Safety standards
Efficiency standards
Rate regulations
Reliability standards
Consumer protections,
Data privacy laws
Land use and environmental impact assessments
Emergency preparedness standards.
Meeting all these requirements places a tremendous burden on energy companies. AI can help by proactively monitoring operations and flagging when an organization is at risk for non-compliance. AI models can also help evaluate risks, and generative AI can offer suggestions for mitigating those risks.
3. Building cyber resilience
Energy companies are extremely vulnerable to cyberattacks. In addition to the usual cybercriminals looking for ways to make money, utilities must often fend off attacks from terrorists and nation-states seeking to disrupt economies.According to the International Energy Agency4: “Cyberattacks on utilities have been growing rapidly since 2018, reaching alarmingly high levels in 2022 following Russia’s invasion of Ukraine. Recent cyberattacks in the electricity sector have disabled remote controls for wind farms, disrupted prepaid meters due to unavailable IT systems and led to recurrent data breaches involving client names, addresses, bank account information and phone numbers.”
The most advanced cybersecurity tools rely heavily on AI to detect anomalous activity in corporate networks. While older tools were often limited to being able to repel attacks that have previously been seen, this next generation of AI-based tools can identify and mitigate brand-new attacks that have never been seen before.
4. Meeting customer expectations
Today’s energy customers have very high expectations. They want their utilities to become more sustainable, and they want suggestions for how to become more energy efficient. They demand personalized service and immediate answers to questions.
AI tools enable utilities to provide personalized recommendations and answer customer questions quickly, even during emergencies when customer call centers become overwhelmed. This opens up opportunities to improve overall customer satisfaction.
AI challenges for the energy sector
While AI and generative AI offer tremendous opportunities, they also come with challenges. Utilities need to make sure that AI deployments meet their obligations to protect customer privacy.In addition, to enable AI, organizations need to have the right kind of storage infrastructure. As explained in a previous CIO.com article5, data is the fuel that powers AI capabilities, and storage is the tank that stores that fuel. Without the right storage, AI processing can come to a halt.
In many cases, the data storage systems that utilities have today are not the systems needed to enable AI. They need state-of-the-art capabilities like distributed storage, data compression, and efficient data indexing that enable the speed and scale AI requires. That’s important because AI and generative AI are tools that can help accelerate solutions to some of the energy sector’s toughest challenges.
Future-focused AI and generative AI
Navigating multiple challenges isn’t easy in any industry. In the energy sector, there is no shortage of problems to solve. Energy organizations are turning to AI and generative AI to help catalyze resolutions to some of their most pressing issues, showing the innovation and resilience that are hallmarks of a future-focused industry.
Read about unstructured data storage solutions and find out how they can enable AI technology.
Intel and Dell are founding members of the vPAC Alliance, a formal coalition of utilities and industry partners coming together to transform our electrical grids. The Alliance is driving a standards-based, open, interoperable and secure software-defined infrastructure to host protection, automation and control solutions for power system substations.
1 https://www.globenewswire.com/en/news-release/2023/05/29/2677606/28124/en/Artificial-Intelligence-AI-in-Energy-and-Power-Market-Report-2023-Sector-to-Reach-14-52-Billion-by-2028-at-a-24-6-CAGR.html#:~:text=AI%20in%20energy%20and%20power,(AI)%20as%20a%20tool.
2 https://www.idc.com/getdoc.jsp?containerId=US508521233 https://www.cnbc.com/2023/02/17/why-americas-outdated-energy-grid-is-a-climate-problem.html
3 https://www.cnbc.com/2023/02/17/why-americas-outdated-energy-grid-is-a-climate-problem.html
4 https://www.iea.org/commentaries/cybersecurity-is-the-power-system-lagging-behind
5 https://www.cio.com/article/649113/accelerating-generative-ai-requires-the-right-storage.html
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