As the global transition to renewables accelerates, traditional energy systems are struggling to manage complex, distributed assets. In response, AI, digital twins, energy management systems (EMS) and the Internet of Things (IoT) are becoming essential for improving efficiency, resilience and control across the sector.
The International Energy Agency expects solar to lead renewable power by 2029, followed by wind in 2030. Yet challenges persist, from intermittent supply and ageing infrastructure to regulatory complexity and high maintenance costs, especially offshore. For many operators, siloed data and limited asset visibility restrict predictive analytics and operational optimisation.
AI plays a central role in addressing these issues. By integrating weather forecasts, sensor data and grid demand, it enables real-time diagnostics, generation forecasting and automated dispatch. Wind farms, for example, use AI to adjust blade alignment for greater efficiency, while hydro plants integrate flow data for smarter energy delivery. These capabilities improve market performance and reduce imbalance penalties.
Major companies are investing in AI-powered energy systems. Amazon is applying machine learning to enhance battery storage and solar output, reflecting wider efforts to cut emissions from data centres and electrified transport.
Digital twins — virtual replicas of physical infrastructure — support predictive maintenance by simulating real-world wear, helping to avoid costly breakdowns. They are especially valuable for remote assets like offshore wind farms. Cities are also adopting digital twins to manage urban infrastructure and energy systems, with more than 500 expected to implement them by 2025.
At the system level, next-generation SCADA and EMS platforms are key to managing distributed resources. A tailored EMS recently delivered a 30 percent drop in energy losses for a solar operator, while halving the need for on-site technicians. Combined with IoT sensors and local data processing, these systems improve response times and allow secure, low-latency control even in remote locations.
Simulation tools help de-risk projects by testing grid integration before deployment. Meanwhile, automated compliance tools support ESG reporting and unlock access to green finance, turning regulation into a competitive advantage.
Digital transformation, however, demands customised rollouts. Many firms adopt modular approaches, beginning with predictive maintenance or reporting automation. Skills shortages can be addressed through embedded diagnostics and alert systems that support remote monitoring and reduce reliance on site-based expertise.
The UK is well placed to lead this evolution. Investments in AI, digital twins and EMS technology can enhance asset performance, ensure regulatory alignment and drive down costs. With scalable platforms and growing digital capabilities, UK energy providers can advance a smart, secure and sustainable green energy future.
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