Transformers, substations + the grid
AI-enabled smart grids are transforming energy production and distribution through real-time predictive analytics and machine learning, dynamically aligning supply with demand. AI is changing grid ecosystems, optimising operations, bolstering reliability and strengthening resilience. By integrating IoT-embedded infrastructure with advanced forecasting and optimisation systems, utilities gain greater eiciency, adaptability, and robustness. This is the view of Global Data, a leading research, intelligence and productivity platform. AI-enabled smart grids and the clean energy shift
A s AI-powered models project demand at micro- scales, empowering utilities to fine-tune load balancing, smart grids are set to reshape the power sector by facilitating the transition to cleaner energy and enhancing reliability. GlobalData’s latest report, Smart Grid: Strategic Intelligence , indicates that AI serves as the intelligence behind smart grids, driving optimisation, stability, and security across energy networks. It cites specific examples in companies such as Solcast and RisingStack using AI and satellite imagery to assess current solar irradiance and forecast
Global Data’s projected investment in transmission networks globally to 2030.
EV integration is increasingly recognised as one of the key drivers in smart grid evolution, enabling a more flexible, resilient, and clean energy system. For instance, GNA Energy (India) launched GNAi, an AI-powered platform for grid optimisation and smart meter integration in 2026. Shiledar adds: “Smart grid technologies are transforming the power sector by making electricity systems more adaptive, eicient, and sustainable. Smart meters and sensors enable real-time monitoring of power flows, helping utilities better balance supply and demand and reduce energy waste.” Utilities such as EDF are using Distributed Energy Resource Management Systems (DERMS) to integrate solar panels, wind farms, and battery storage more smoothly into the grid, mitigating issues like voltage spikes and frequency fluctuations. Another example is virtual power plants (VPPs), which aggregate resources like residential solar panels, EV batteries, and flexible industrial loads to act as a single controllable asset for grid operators. Xcel Energy’s advanced VPP in collaboration with Itron and Tesla integrates residential battery systems, roo£op solar, EV chargers, and smart thermostats into Itron’s IntelliFLEX DERMS platform, enabling the aggregation and dispatch of DERs during peak load to stabilise the grid. In closing Shiledar says: “As renewable energy grows and electrification spreads through EVs, heat pumps, and more, the grid must evolve. Smart grid tools drive this evolution through automation, digital intelligence, and two-way communication. In essence, these solutions bolster energy security, cost eiciency, and ecological integrity, fostering a sustainable energy ecosystem.”
PV output, helping grid operators curtail less and schedule reserves more eectively. Likewise, Hornsdale Wind Farm’s AI systems, using atmospheric and performance data, are significantly improving forecasting accuracy, enabling better anticipation of variability and avoiding wasted capacity. Additionally, utilities such as National Grid harness sensor data to monitor critical systems and predict failures, significantly cutting downtime. Rehaan Shiledar, Power Analyst at GlobalData, comments: “Government initiatives, renewable integration, the demand for a more resilient and eicient grid, and technologies such as smart meters, AI, and IoT are driving investment in the power transmission market. Global transmission investment in 2025 stood at $378.3 billion, increasing by 10.1% over 2024. The investment was primarily in substations at $274.3 billion, followed by transmission lines at $104 billion. The transmission investment is estimated to grow from $378.3 billion in 2025 to $586 billion in 2030 at a compound annual growth rate (CAGR) of 9.2%.” Technological trends in the smart grid, particularly digital twins, microgrid development, and electric vehicle (EV) integration, are evolving rapidly to improve grid resilience, eiciency, and sustainability. These technologies are converging to create a more dynamic, decentralised and intelligent power system that can handle the complexities of renewable energy and bidirectional energy flow. Companies such as ABB Electrification are enhancing grid eiciency, resilience, and accelerating the energy transition through Enline’s Digital Twin modelling and Dynamic Line Rating (DLR) to improve transmission and distribution networks. Hitachi Energy and GE Vernova are supporting microgrid growth through distribution automation, grid control so£ware, and integration of distributed energy resources and storage.
For more information visit: www.globaldata.com
26 Electricity + Control JUNE 2026
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