Smarter Grids, Stronger Utilities - Energy Intelligence

Sansoen Saengsakaorat/Shutterstock Save for later Print Download Share LinkedIn Twitter The centralized one-way generate and deliver power model is fast fading into history, as every day it is challenged by demanding customers and new and even more demanding artificial intelligence data centers. But while the days of a fully autonomous grid are still a way in the future, the intelligent smart grid powered by industrial AI, predictive analytics and an empowered workforce is very much here today. It’s taking energy and utilities far beyond simple decarbonization goals — it’s improving reliability, affordability and safety.Historically, electricity grids were relatively predictable systems. Power flowed in one direction, from centralized generation facilities through transmission and distribution networks to homes and businesses. Utilities owned the assets, controlled the flow and could largely manage the system through centralized planning and human oversight.That model no longer exists, and utilities face a whole new set of emerging and worsening threats — rising electricity demand from power-hungry data centers, infrastructure that continues to surpass intended lifecycles and retiring workforces taking years of tacit knowledge with them.Leveling the Energy Playing FieldPreviously, energy pressures have often skewed toward a specific goal. In recent years, sustainability has dominated company agendas as governments and regulators pushed utilities to reduce emissions and accelerate decarbonization efforts.Today, there’s a rebalance of priorities stemming from rising energy costs, growing electricity demand from AI-driven data centers and increasing concerns around grid resilience considering recent extreme weather events. With growing demand for energy independence, and security in the wake of global geopolitical shifts, the focus is now on reliability, affordability, safety, and sustainability, because globally, unreliable, unstable power isn’t an option.New ComplexitiesThe rapid rise of distributed energy resources — rooftop solar, battery storage, electric vehicle charging, microgrids and decentralized generation — has transformed the grid into a far more dynamic and complex environment. While utilities still own 80%-90% of grid assets, some may now be managing two-way energy flows across assets they do not fully own or control.The amount of flowing data is too much for humans to consume and take action on alone. An issue out in the field may require a technician to interact with third parties to coordinate access and safety while working on the lines where two-way energy flows exist.Smart grids can not only make split-second decisions — far quicker than humans could make at such a scale — they can also detect infrequent issues, analyze large amounts of data and make recommendations on corrective actions, even executing actions if authorized to do so without a human in the loop. Automated intelligence capable of processing vast streams of operational data in real time — such as smart devices out in the field — allow utilities to send commands and real-time adjustments to keep the grid running, stable and harmonized.There are hurdles along the way — four in particular — that will need to be dealt with, and here’s how:1. Data, data, data … and more big data, but what should utilities do with it?The utilities sector has never had a lack of data. For decades, the sector has been collecting an overwhelming amount of information from substations, field assets, meters and control systems. The problem has been turning this siloed big data into timely, actionable decisions.With internet of things (IOT) and automated smart-grid technology, sifting through this mass of data becomes much easier. Utilities can begin identifying meaningful operational signals hidden within enormous datasets. AI and predictive analytics can sift through huge volumes of operational data, identify patterns, and predict where failures are likely to occur next. From a workforce perspective, utilities can prioritize work that requires immediate attention while safely deferring others.2. Locating a starting point is easier said than done.Utilities need to make sure this analyzed data is accurate and reliable, but this alone is not enough. Companies must ensure that the data is from the correct sources to make an informed decision. It’s about identifying the right starting point of data, while ensuring consistent data that is cleaned through good data hygiene.But the operational benefits are worth it. Instead of relying on manual inspections every few years, utilities can use intelligent, connected assets that continuously self-monitor and report issues as they happen. This delivers two key benefits: improved reliability and enhanced safety.24-7 monitoring and IOT-enabled assets enables utilities to detect anomalies that humans might miss, especially intermittent faults that only occur under certain conditions.From a planning perspective, early warning signs for one asset can be extrapolated to similar assets for replacement or maintenance way before issues or downtime occurs. Industrial AI and predictive analytics then ensure maintenance schedules are continually optimized and that assets are repaired or replaced at the right time.3. Addressing the technology brain drain, empowering the workforce.Utilities are also battling a less visible but equally serious challenge — the loss of institutional knowledge. Large portions of the experienced workforce are approaching retirement, and utilities are struggling to compete with major technology firms for data scientists, AI specialists and digital engineers.Unlike hyperscalers and technology giants such as AWS and Google, utilities operate within heavily regulated environments with limited flexibility, which makes recruitment and retention of workers with IT skills increasingly difficult. Moreover, they are also struggling to retain the knowledge of operational staff in the field. Current projections show over 106,000 professionals are expected to retire in the next five years, the equivalent of a loss of 17% of the UK utilities workforce at large.It’s not about replacing staff, it’s about augmenting the workforce experience. Utilities are now beginning to explore how AI systems can capture decades of institutional knowledge and make it accessible to newer employees in real-time. Out in the field, this could give less-experienced field technicians real-time guidance and step-by-step instructions during complex maintenance procedures. These ready-made tools reduce the need for technical expertise, too, with the ability to automatically analyze sounds, images and observations, comparing them against historical data and manuals and recommending likely fixes.For example, IFS Resolve calls in digital workers to sift through huge data volumes to analyze and flag issues, aid troubleshooting and identify resolutions based on previous repairs. From a wider recruitment perspective, employees become more productive, empowered and efficient, enabling utilities to do more with fewer people while improving operational decision-making.4. A distributed IOT-led grid is a vulnerable one: time to get smart(er) on cybersecurity.With staff shortages, and an increasing number of workers leaving the industry, reliance on digitally driven operations has only increased, which opens the floodgates for cybersecurity attacks.The more technology introduced, the smarter these assets become, but also way more vulnerable. Connected devices — from smart meters to automated substations — introduce additional cybersecurity exposure. As utilities deploy more IOT-enabled infrastructure, cybersecurity is no longer confined to the IT department of a utility.Now that everything is smarter, IT protection needs to be, too. Investing in a solution with embedded advanced security controls is nonnegotiable for navigating today’s smart grid. From role-based permissions to detailed audit logs, advanced solutions will help utilities reduce cyber risk, prevent fraud and support regulatory requirements all within a centralized platform.Utilities will need to be less reactive and more proactive operationally and from a planning perspective. And remember that energy infrastructure is too critical, too regulated and too complex to remove humans from decision-making processes.The technology is there to enable utilities to modernize without compromising reliability, to scale innovation without increasing operational fragility and to deploy industrial AI in ways that enhance, rather than replace, human expertise.The autonomous grid may still be years away, but the smart grid is already here.Carol Johnston is vice president of industries, energy, utilities, and resources, at IFS, a global provider of cloud-based enterprise software. The views expressed in this article are those of the author.