How Core Technology is Forging the Smart Grid’s Future

Digital transformation is revolutionising the electricity grid, making it smarter, more flexible and capable of real-time monitoring and management. Smart grids integrate advanced digital technologies — such as sensors, data analytics, AI and automation — to optimise energy distribution, enhance reliability and empower consumers. 

Unlike traditional grids, which were built for one-way electricity delivery from centralised power plants, smart grids enable two-way communication between producers and consumers, creating a responsive, adaptive energy ecosystem.

This modernisation of the grid is crucial to meeting rising global energy demand and accelerating the transition to renewable energy sources. Smart grids play a pivotal role in decarbonising energy systems and supporting sustainable development and are an essential component of the broader energy transition challenge.

AI’s transformative impact

AI is undoubtedly having a transformative impact on smart grids. In its Patents for Enhanced Electricity Grids study, conducted alongside the European Patent Office (EPO), the International Energy Agency (IEA) highlights that AI is driving major advances by enhancing predictive capabilities, improving fault detection and enabling more flexible network operations to meet fluctuating power demands.

The study says that the US and China are leading the way in AI for smart grid development, with AI-related patents growing sixfold since 2018. The technology’s main role, it finds, is in advanced forecasting and decision-making, with 39% of AI patents focusing on predicting electricity demand and managing supply. 

AI is also driving innovation in microgrids, outage detection and fault management, enabling real-time, data-driven grid operations, making networks more intelligent, automated and adaptable to complex conditions. 

The grids’ digital nervous system

The evolution of smart grids begins with creating a digital nervous system enabled by the Internet of Things (IoT), where thousands of sensors constantly collect real-time data across the grid to monitor conditions such as voltage, frequency and load. This constant flow of information allows grid operators to respond instantly to changes in demand and supply.

Leading companies like Siemens, Itron and Cisco are at the forefront, developing integrated solutions combining smart meters, communication networks and AI-driven analytics, enabling dynamic grid management.

Siemens, for example, has worked on large-scale smart grid projects in Germany and the US, implementing AI-driven energy management platforms capable of predictive maintenance and self-healing network functions. 

Cisco provides the secure IP-based networking infrastructure that connects grid nodes and Itron delivers smart metering technologies to utilities around the world. ABB’s digital substations and grid automation software are used in projects from Scandinavia to India, integrating renewables while improving stability.

As well as this, Schneider Electric’s EcoStruxure Grid platform helps utilities manage distributed energy at scale, using real-time analytics to improve reliability.

By leveraging AI and advanced software like its EcoStruxure platform – which enhances grid infrastructure and digitises operations to make grids smarter, more resilient and adaptable to today’s complex energy demands – Schneider Electric is empowering grid operators to future‑proof critical infrastructure.

Philippe Arsonneau, SVP of Schneider Electric’s Infrastructure Segment, says that many grids were originally built over a century ago for centralised energy systems, but today’s needs for electrification and distributed energy resources (DERs) require a fundamentally different approach. 

“The grid is really the central enabler for a decarbonised world and for more electrification,” he says. “At Schneider Electric, we’re enhancing grid infrastructure, digitising the grid and making it much smarter than it was when it was built.”

Philippe highlights digital technologies’ role in providing visibility and predictive capabilities to manage variable renewable energy. 

He adds: “Being able to use digital and software applications like distributed energy resource management (DERMS) means we are able to deviate power or be predictive in our demand response. This means we’re making traditional infrastructure much smarter as well as building out for the future.”

EcoStruxure DERMS, for example, effectively manages solar farms, wind farms and microgrids while incorporating virtual substation technology. He says: “We're actually leveraging technology and software like DERMS to enhance the grid, optimising the management of electricity flow.”

Facing smart grid challenges

However, challenges remain in cybersecurity, data interoperability and scaling infrastructure to handle increasing decentralised energy resources and variable renewable inputs.

Siemens, for instance, recognises that the explosive growth in AI workloads is fundamentally changing the power and sustainability landscape for data centres.

According to Ciaran Flanagan, Siemens’ Vice President and Global Head of Data Centre Solutions and Services, the industry is facing unprecedented challenges due to soaring power densities — some server racks now exceed 100kW — requiring a complete rethinking of power distribution, cooling and safety systems.

“Time to power has become a critical bottleneck in the industry, especially when deploying new facilities,” he says.

“Grid connection backlogs are stretching into years, with many operators facing MW/GW-scale connection delays or outright rejections. In response, leading operators are taking control of their destiny by either developing on-site generation capabilities with microgrids or forming strategic partnerships with utility providers. At some point, data centres will become part of the grid ecosystem.”

How smart buildings give back to the grid

Much like data centres, buildings can put immense pressure on the grid. But by retrofitting them with building-to-grid (B2G) technology – turning them into smart buildings – they are evolving from passive energy burdens into intelligent assets.

Making a building intelligent requires a fundamental technological overhaul, moving it from a passive structure to a dynamic, data-driven ecosystem that can even generate revenue by selling electricity back to the grid.

The surge of information created by the likes of IoT sensors feeds the system’s brain: an AI-powered platform that creates a digital twin.

The AI uses this model not just to see what’s happening, but to predict what will happen.

By integrating external data like weather forecasts, energy prices and even occupancy schedules, it can make proactive decisions, moving beyond the simple “on/off” paradigm. 

This core stack of IoT sensors providing data and AI providing intelligence is the foundational technology that unlocks a building’s potential.

To put this into context, Johnson Controls’ advanced digital platforms are capable of processing up to a million data points each minute, enabling buildings to intelligently adapt in real time based on factors like occupancy levels, changing weather and fluctuating energy costs.

Katie McGinty, the firm’s Vice President and Chief Sustainability and External Relations Officer, says Johnson Controls tech at Stanford University has led to a 20% reduction in peak energy demand and generated yearly savings of US$500,000.

“We can achieve on the order of 10% to 20% additional emission reductions, even for brand new buildings and those with the highest level of green certification,” Katie says.

“When those buildings were inaugurated and initiated, they may have been tuned so that they had the highest level of green performance, but over time those set points get changed or those set points migrate.”

Here, the transition back to the main smart grid narrative is critical: smart buildings aren’t just isolated efficiency upgrades, but are becoming distributed energy resources capable of balancing load, providing storage and supplying power when the grid most needs it.

In short, the same intelligence transforming grid operations is now embedded at the level of individual buildings — making every node in the network smarter and more responsive.

Curating the grid of the future

The journey from centralised, one-way energy delivery to an intelligent, interactive smart grid is well underway as AI, IoT and advanced analytics optimise existing systems and redefine the relationship between generation, distribution and consumption.

Sensor‑dense IoT architectures are creating a continuous data layer across the grid, enabling millisecond-by-millisecond awareness.

Edge computing and AI models — from advanced forecasting algorithms to reinforcement learning optimisers — are turning that data into predictive, automated control decisions.

The smart grid of the future is less a single piece of infrastructure and more a distributed, software‑defined platform — one where every sensor, node and algorithm contributes to a resilient, high‑efficiency, low‑carbon energy network.

Read this feature in the August edition of Technology Magazine by clicking here.