The Promise and Perils of Artificial Intelligence for the Energy Transition

Artificial Intelligence (AI) offers remarkable promise for the energy transition – with opportunities to strengthen resilience, accelerate decarbonization, and transform the way we operate the grid. But AI also brings huge challenges – chief among them energy consumption, cybersecurity, and organizational change. How can leaders in clean energy leverage AI strategically and ethically while preparing for a future where AI is integral to our industry? 

The energy sector today is experiencing profound transformation, and one of the drivers of this change is artificial intelligence (AI). As global climate change intensifies and energy demands grow, AI offers unprecedented opportunities to build resilience, accelerate decarbonization, and unlock operational efficiency. 

But embracing AI’s potential means we must also navigate its risks. For clean energy leaders, this is a pivotal moment to define how your organization intends to respond to an AI-driven future – and prepare in a way that aligns teams rather than distracts from core business objectives.

AI as a Catalyst for Resilience in the Energy Sector

The energy industry has always grappled with volatility, whether from shifting demand patterns, climate-related disruptions, or the complexities of integrating renewable energy into an ever more volatile grid. Used wisely, AI can help tackle these challenges head-on, fundamentally reshaping how the sector operates.

One of AI’s earliest applications has been predictive maintenance. By analyzing real-time data from equipment, AI systems can detect potential failures before they occur, reducing costly downtimes and improving overall reliability. For example, wind turbines equipped with AI sensors can identify wear and tear in components, enabling timely repairs and maximizing energy output.

AI also plays a critical role in enhancing forecasting accuracy. Traditional methods of predicting weather and energy demand often fall short in today’s climatic mood swings. This is an area where AI-powered models can excel -- analyzing complex datasets to deliver more precise forecasts, ensuring that renewable energy systems like solar and wind farms operate at peak efficiency.

Another area of AI potential for the energy transition is real-time adaptability for grid stability. AI can help balance supply and demand, preventing blackouts and ensuring consistent energy delivery. By enabling systems to respond dynamically to changing conditions, AI enhances both flexibility and resilience.

Balancing the Rewards and Risks of AI

While AI’s potential is vast, its use in accelerating the energy transition is not without risks. As an industry, we must weigh the rewards against potential challenges to ensure that the implementation of AI is ethical, sustainable and supportive of business objectives.

The Rewards

As noted, AI has the potential to drive significant gains in the energy sector. AI can reduce maintenance costs and improves energy forecasting, enabling more effective storage and distribution. For instance, AI algorithms can predict periods of high energy demand and preemptively adjust the grid or storage systems to accommodate fluctuations. These capabilities not only enhance operational performance but also accelerate the transition to a low-carbon future.

AI also empowers decarbonization efforts by maximizing the efficiency of renewable energy systems. In solar farms, for example, AI-driven tracking systems can optimize panel alignment based on weather conditions, increasing energy production by as much as 7%. Similarly, in wind farms, AI models enhance power forecasting accuracy, reducing errors by up to 30%.

The Risks

However, AI also introduces new challenges that demand careful attention. Cybersecurity and data privacy are top concerns, as increased digitization makes critical energy infrastructure vulnerable to attacks. According to Data Dynamics, a staggering 83% of energy organizations have experienced data breaches, underscoring the importance of robust cybersecurity measures. As AI becomes more integrated into energy operations, leaders must prioritize ethical AI use and robust data governance. This includes ensuring transparency in AI decision-making processes, addressing potential biases in AI models, and safeguarding data privacy.

AI’s own energy consumption poses another challenge. Training AI models requires significant computational power, which can offset the environmental benefits they enable. At the 2024 ASME Power Conference, AI took center stage as Geraldine Richmond, Undersecretary for Science and Innovation at the Department of Energy, framed the energy challenge of AI this way: “Today, data centers that take 4 percent of our energy will use 9 percent by 2030 -- that’s a huge jump,” Dr. Richmond noted. “That’s why we have a number of initiatives at the Department of Energy and worldwide to make sure we can meet the power needs for AI as well as EVs and all the new manufacturing that’s coming to the U.S.”

One of the ways to mitigate this massive increase in power consumption is for organizations to prioritize co-locating AI systems with renewable energy sources, such as EDP wind and solar farms. Additionally, "dispatchable computing" can schedule AI computations during periods of abundant renewable energy, aligning AI energy use with green energy availability. Companies like EDP are well-positioned to shape the landscape of data center infrastructure and ensure its sustainable development. Strategic partnerships between AI infrastructure providers and the renewable energy sector can turn this energy consumption risk into a win-win scenario, advancing the energy transition.

The Leadership Imperative: Preparing Teams for AI

As AI reshapes the energy sector, leaders must play a guiding role in steering organizations through this transformation. It’s not just about adopting AI technologies but also about aligning business processes, upskilling teams, and fostering a culture of innovation and collaboration.

Reshaping Processes 

To fully leverage AI, organizations need to reimagine their workflows. This involves embedding AI into every layer of operations, from project management to resource allocation to energy production and distribution.

Training Teams 

AI adoption requires a workforce that understands its potential and limitations. Comprehensive training programs tailored to different roles are essential. Engineers, for instance, may need to learn how to interpret AI-generated insights, while executives must focus on strategic applications and ethical considerations, as well as cybersecurity concerns. 

Fostering Collaboration 

AI thrives in environments where diverse teams work together. Energy companies should encourage cross-functional collaboration between AI experts, engineers, and policymakers to ensure well-rounded solutions. Strategic partnerships with technology firms and academic institutions can further enhance AI capabilities. 

Promoting Ethical AI 

Ethics should not be an afterthought in AI deployment. Establishing robust data governance frameworks, ensuring transparency in AI systems, and adhering to privacy standards are critical for building trust with stakeholders. 

EDP’s AI Vision: Turning Data into Power

EDP offers a compelling example of how energy companies can embrace AI strategically. Guided by the vision to “turn data into power and intelligence into action,” EDP has identified key areas where AI delivers the most value for the company, its customers and for the power grid itself. 

Key EDP Projects 

• Electricity Demand Forecasting (PREDIS): Predicting energy demand with high accuracy, improving the balance between energy supply and demand to improve grid reliability
• EV Charging Demand Prediction (ElectricDots): Optimizing the location and adoption of new electric vehicle charging stations by predicting demand rates at any geographical point
• Distributed Solar Simulator: Locating the best rooftops to build more solar and expand distributed generation for our customers
• Generative AI Assistant (Mind4EDP): An internal AI tool that improves project management and workforce productivity  

Foundational Investments 

To support these initiatives, EDP has invested heavily in foundational technologies, including machine learning operations pipelines and a comprehensive AI training program that has already certified more than 500 employees.  

Underscoring the importance of ethics in AI, EDP has defined a Generative AI usage policy that encompasses 10 Golden Rules to ensure its responsible and effective use.EDP has also created a Reference Architecture for Data & AI and launched a comprehensive program to catalogue all data domains at EDP.  By the end of the year, 50% of the domains and data elements will be catalogued, representing 80% of the most important data needs for AI initiatives. 

The Way Forward 

AI is more than a technological tool. Employed with care, AI can be a transformative force that redefines how the energy sector operates. From improving grid resilience to driving decarbonization, AI holds immense promise. However, realizing this potential requires thoughtful leadership and a commitment to ethical practices.  

As organizations navigate the AI era, the question is no longer if they should adopt AI but how they can do so strategically. By blending human ingenuity with AI-powered tools, we can unlock new levels of efficiency and innovation – creating a more resilient, efficient, and sustainable future.