74 INTERVIEW Artificial intelligence is much more than just one technology – it comprises expert systems, machine learning (ML) programmes, prescriptive and prognostic models, reinforcement learning, large language models (LLMs) and generative AI. Jim Chappell, global head of AI and advanced analytics at AVEVA, explains how this broad spectrum of AI technologies work together with the cloud, data management and analytics solutions to provide utility companies with powerful insights and capabilities to optimise their operational sustainability. How is AI being used to make the energy sector more sustainable? AI-infused solutions can turbocharge industries’ progress towards efficiency and sustainability. Although AI has been helping to lower carbon emissions for many years, we have only scratched the surface of its potential in the overall area of sustainability. For example, predictive analytics can quickly identify underperforming assets or incorrect control settings that result in additional fuel being burned and generating excess greenhouse gas emissions. Furthermore, ML systems can help predict energy consumption. For example, data-driven AI can be combined with physics-based simulation to better emulate operations as part of a grey-box modelling system. Carbon capture simulation is another area where AI can support sustainability. AI can also help make renewable and alternative fuels, such as wind and green hydrogen, more economically viable and competitive with traditional sources, thus accelerating the global green energy transition. All of these factors will support industrial companies on their journey to net zero. These types of AI solutions do not involve training massive LLMs, so they don’t consume large volumes of power. In the case of greybox modelling, where AI models replace physics-based models, AI runs substantially faster, thus requiring significantly less energy than its alternative. As AI evolves and becomes more objectivedriven, it will play an ever larger role in climate change control and overall sustainability. This will also include more AI-driven closed-loop control for optimal performance. What types of industrial insights can AI-powered solutions offer? Using AI models trained on various types of historical data allows utility companies to more accurately predict demand, manage varying energy sources, forecast asset failure and fine-tune their operations. For example, AI can analyse sensor data from many types of energy storage systems and zero-carbon power generation, including wind, solar, nuclear, hydroelectric and geothermal. AI can detect problems long before a human or other type of software can, significantly increasing operational efficiency and reliability. In addition, AI can model alternative energy production, including green hydrogen. Large BY REBECCA GIBSON Jim Chappell of AVEVA explains how data and AI can empower organisations in the energy sector to achieve sustainable transformation Will AI make sustainable energy a reality?
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