Artificial intelligence (AI) is positioned to play a transformative role in the energy sector. It offers new ways to improve efficiency, accuracy, and operational responsiveness across both conventional and renewable power systems. This was the message from Atty. Andrea May C. Toyoda, head of Ancillary Services and Energy Management at SN Aboitiz Power Group, during a recent talk entitled “AI and the Future of Energy: Emerging Technologies Reshaping the Sector” in the seminar, “Sustainable Energy Transition: Integrating Efficiency, Innovation, and Renewables” hosted by the Philippine Energy Research and Policy Institute (PERPI)

Toyoda, who also serves on the executive board of the Philippine Energy Research and Policy Institute, emphasized that while many associate AI primarily with generative tools, its broader capabilities- specifically such as machine learning, deep learning, and predictive analytics- are already making significant impacts in the global energy industry.

One compelling example she cited was the experience of VistraCorp, a U.S.-based power company that partnered with McKinsey to introduce AI into its thermal power plant operations. Initially starting with only a single model, the company eventually rolled out over 400 AI models across 67 generating units. 

Among their most successful innovations was the Heat Rate Optimizer, a tool that analyzes both real-time and historical plant data to recommend operational adjustments every 30 minutes. This shift allowed the company to significantly reduce fuel consumption while maintaining energy output, resulting in substantial environmental and economic gains. 

Toyoda noted that VistraCorp was able to cut maintenance costs by up to 30%, increase equipment availability by 20%, and save around USD 60 million annually and all while avoiding 1.6 million tons of carbon emissions each year.

AI’s benefits are not limited to conventional power plants. In the renewable energy space, Toyoda pointed to the work of Google’s DeepMind team, which developed an AI model capable of predicting wind farm output up to 36 hours in advance. By integrating historical turbine performance data with real-time weather forecasts, the system allowed Google’s wind assets to operate more like dispatchable generators. Specifically those that can reliably commit power to the grid ahead of time. The increased predictability not only stabilized output but also raised the market value of their energy by 20 percent.

These international use cases, Toyoda argued, offer a strong case for AI integration in the Philippine energy sector. Although the country is still in the early stages of adopting such technologies, the potential applications are wide-ranging. She noted that the Philippines’ dynamic five-minute wholesale electricity spot market produces vast amounts of data that remain underutilized. With AI, stakeholders, which include generators to policy makers, could better analyze market trends, improve trading strategies, and manage supply and demand in real time.

Toyoda also highlighted the potential for AI to improve grid integration for variable renewable energy, optimize battery energy storage systems, and extend the operational life of aging power plants through predictive maintenance. These advances could reduce support costs, boost reliability, and make the energy system more adaptive to both market and environmental challenges.

“By fully onboarding ourselves with AI, we can harness the benefits of real-time data analytics, reduce support costs, and improve grid stability,” she said.

While she acknowledged that AI remains a polarizing subject in some circles, Toyoda emphasized that its practical benefits for energy operations are clear. Once more she reiterated that it represents a vital step toward a smarter and more sustainable power future.

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