75 advances can be achieved by using AI models intermixed with physics-based simulation. AI black-box models run hundreds of times faster than a corresponding physics model and are much easier to set up, enabling them to identify issues in near-real time. Furthermore, by combining prescriptive, prognostics and predictive analytics, organisations can optimise resource allocation and minimise waste, resulting in significant savings. How can organisations use AI to identify energy-saving opportunities? On the demand side, AI-driven energy management systems are empowering consumers and businesses to take charge of their own energy usage. By analysing consumption patterns and providing personalised recommendations, these applications promote energy efficiency and reduce costs. For example, US-based utility provider Dominion Energy is using AVEVA’s CONNECT Data Services, powered by Microsoft Azure, to collect and share real-time data on energy sources and power flows. This enables customers to track their usage, supporting their progress toward net-zero goals. In what ways can AI help to track and reduce global carbon emissions? AI-powered models can predict the impact of operational changes, enabling companies to make real-time adjustments for efficiency and cost savings. For instance, AVEVA is working with TotalEnergies to monitor over 110 greenhouse gas reduction projects. Data from various global operational sites is fed “ As AI evolves and becomes more objective-driven, it will play an ever larger role in climate change control”
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