Feature: Industrial
timely operational decisions. By bringing together energy, operational and asset data, organisations gain a clearer understanding of how their electrical infrastructure is performing and where greater flexibility and efficiency can be achieved.
Managing electricity demand Consider a building or a facility adding EV charging and electric heating. At first glance, this may appear to require a larger grid connection or major investment in new electrical infrastructure. In reality, the constraint is oſten not total capacity, but when demand occurs. Multiple high- power loads operating simultaneously can create short-duration peaks that exceed available capacity, even when overall daily energy consumption remains well within acceptable limits. An intelligent electrical distribution
system can help address this challenge by understanding how loads interact and coordinating them more effectively. EV charging can be scheduled dynamically according to available capacity. HVAC systems can respond to occupancy and environmental conditions while avoiding unnecessary demand spikes. Battery storage, where installed, can support short periods of high demand before recharging during quieter periods. Tese adjustments are largely invisible
to building occupants but can significantly improve infrastructure utilisation while avoiding unnecessary investment in additional network capacity. Te same principles apply across commercial buildings, hospitals and data centres.
Building a more resilient electricity system Many of today’s capacity constraints exist much closer to consumers. Local substations, distribution transformers and low-voltage feeders all have finite capacity. When neighbouring buildings simultaneously increase demand, local infrastructure experiences the greatest strain. Building more generation alone does not
resolve these constraints. Greater flexibility is also needed within the electrical systems connected to the network. When buildings
By bringing together energy, operational and asset data, organisations gain a clearer understanding of how their electrical infrastructure is performing
can stagger flexible loads and make better use of existing infrastructure, they collectively contribute to a more resilient electricity system. In this sense, energy intelligence
benefits not only individual buildings but also the wider grid. It allows buildings to become active participants in balancing demand while providing engineers with greater operational visibility throughout the lifecycle of an installation. It creates a connected system capable of adapting to changing operating conditions and supporting a more flexible energy network. As our energy system becomes more
distributed and complex, future flexibility is becoming just as important as installed capacity. Intelligent electrical systems can be upgraded incrementally rather than requiring wholesale replacement, allowing buildings to evolve alongside changing energy demands. Tis is key to improving the efficiency, resilience and longevity of last-mile electrical distribution.
Improving maintenance Electrical assets naturally degrade over time, but conventional maintenance often relies on periodic inspections or fixed service intervals. While effective, these approaches can’t always identify developing issues between inspection cycles. Continuous monitoring provides
a different perspective. Changes in current, voltage, temperature, power quality or switching behaviour can provide early indications that equipment performance is changing. By analysing these trends over time, engineers can identify potential problems before they result in unplanned failures, allowing maintenance to be planned around
actual equipment condition rather than predetermined schedules. Tis approach is particularly valuable in
environments where electrical reliability is business critical, such as manufacturing, healthcare, transport and data centres, where unplanned downtime carries significant operational and financial consequences.
Grounded in operational data Artificial intelligence is expected to play an increasingly important role in analysing growing volumes of operational data. However, general-purpose AI alone lacks the physical understanding required for mission-critical electrical infrastructure. Effective energy intelligence depends on hardware performance models built on accurate operational data from connected assets. When intelligence is grounded in physical reality rather than assumptions, it becomes a practical engineering tool that helps anticipate issues, optimise performance and support better operational decisions. For over a century, the primary role
of low-voltage electrical distribution has been to deliver power safely and reliably. Tat responsibility remains unchanged. What is changing is the expectation that electrical infrastructure should also provide operational insight, support flexible energy use and strengthen the resilience of both buildings and the wider electricity system. As electrification accelerates, energy
intelligence at the point of use will become as fundamental to electrical distribution as protection, reliability and power quality are today. Te next generation of electrical infrastructure must not only distribute power safely and efficiently, but also provide the operational intelligence needed to make better use of every available kilowatt.
www.electronicsworld.co.uk November 2026 35
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