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Harald Remmert

Innovation

The Benefits of Digital Twins in Utilities

Why virtual replicas of physical objects and processes enable greater operational efficiency

Published: Thursday, September 7, 2023 - 11:02

William Thomson, Lord Kelvin, once said that what he could measure he could control. Other variations of this saying are, “If you can’t measure it, you can’t improve it,” or, “To measure is to know.” In a highly intricate and delicate industry like utilities, it’s challenging to have reliable control over energy production and consumption without technology solutions, such as digital twins, that enable reliable means of measurement and modeling for improved operational efficiency.

A digital twin is a virtual representation that serves as a real-time replica of a physical object or process. While such a concept may sound advanced, digital twins are nothing new. In fact, 50 years ago (30 years before the term was coined), NASA used a solution thought to be the earliest instance of digital-twin usage to fix the damaged Apollo 13 spacecraft. Experts will even point to an older example, in the form of a train station track board that used lights to indicate train tracks, track switches, signals, and the positions of trains.

Today, digital twins play a crucial role in enhancing the performance of electric, water, and gas utilities, and offer many transformative benefits, from real-time insights and data-driven decision making to predictive maintenance and asset management.

Digital-twin use cases in electric, water, and gas utilities

Electric utilities use digital twins to improve several key processes. In grid management, digital twins create models of electric grids, including power generation, transmission lines, and distribution networks, that give electric companies real-time visibility of performance as well as insights into potential issues. This protects assets from damage, such as lightning strikes. Digital twins also help electric utilities monitor the health and performance of transformers, substations, and other assets, permitting them to adjust maintenance schedules to reflect future needs.


By digitizing a system and building digital-twin models, utilities can play “what if,” increasing pressure here and tweaking temperature there, simulating what will happen downstream before they actually implement a change in real life. Credit: arbyreed

Additionally, electric companies can run simulations with digital twins to predict future power consumption, allowing them to load balance accordingly to ensure operational efficiency, which reduces the risks of brownouts and blackouts.

Consider an unknown defect in the electric grid that could result in a blown transformer: With digital-twin technology, electric utilities can run simulations to uncover this defect and test what would happen to the grid under certain load conditions. This information helps companies optimize the grid so that even if a transformer goes down, it’s resilient enough to stave off any major outages.

Similarly, water and gas utilities leverage digital twins to enhance systems and reduce costs. For example, water utilities use digital twins to simulate water distribution systems, helping them monitor water flow, pressure, and quality while uncovering leaks to decrease loss. For gas utilities, digital twins create virtual representations of pipelines, which aids efforts to search for corrosion and leaks. This promotes early detection, minimizing accidents and ensuring greater asset longevity. Furthermore, the data provided by digital-twin technology support both water and gas utilities to more effectively comply with safety and environmental regulations.

Predictive maintenance, improved efficiency, and risk mitigation

Another benefit of digital-twin technology is that utilities can use it to perform predictive maintenance. An IoT-enabled method, predictive maintenance empowers companies to use statistical analysis and historical data to determine whether a machine requires maintenance or enhancement. While predictive maintenance is still nascent, utility companies can employ digital-twin technology to create models of their machines, helping them uncover patterns, make accurate predictions and, when necessary, intervene to fix problems. This can safeguard operational efficiency, reducing downtime and optimizing maintenance costs.

Digital twins help utilities spot anomalies and inefficiencies not only in machines but also in processes. Digital twins provide a holistic view of operations, giving utilities access to more information for data-driven decision making. Imagine someone trying to verify that their refrigerator has a consistent temperature. If they only measure the temperature once a day at the same time every day, they may get a consistent reading and assume everything is OK. However, when they measure throughout the day, they might notice that the temperature fluctuates outside of normal parameters, indicating a problem. In the same way, utility companies can use digital twins to measure a host of variables in real time and on a fine-grained timescale, allowing them to identify operational inefficiencies and optimize processes.

Beyond boosting operational efficiency, digital twins serve as powerful tools for risk mitigation. By digitizing a system and building digital-twin models, utilities can play “what if,” increasing pressure here and tweaking temperature there, simulating what will happen downstream before they actually implement a change in real life. In some scenarios, they might discover that such changes could be catastrophic. Thankfully, companies can run multiple simulations until they find the safest parameters for success. This ongoing feedback loop increases the turnaround of new changes while anticipating and managing potential risks.

The necessity of connectivity

Connectivity is foundational to real-time data collection. Consider, for example, that power grids are getting more dynamic, thanks to the emergence of microproducers (e.g., solar, wind, water) and energy storage systems (batteries, thermal). These microproducers can work at an excess capacity on sunny or windy days, but they underproduce on days with unfavorable weather. As such, the ability to model and predict weather conditions using digital twins based on real-time forecasts is invaluable. However, these capabilities are only possible if a producer has the proper telemetry throughout the grid.

Indeed, without reliable connectivity, the benefits of digital-twin technology are unavailable. For companies to even collect the data generated by their machines and meters, they need uplink connectivity, including a path to a cloud to store the data. To that end, utilities should implement a connectivity solution that is robust enough to function in environments with harsh conditions—Digi’s industrial routers, for example, are built to withstand extreme temperatures and humidity, including punishing vibrations and electric shocks. These solutions also must be secure throughout a product’s life to protect against an ever-increasing number of cyberthreats.

Digital transformation

Utilities can remain competitive and ensure continuous service to constituents by adopting digital-twin technology, which will play a key role in the larger shift toward digital transformation. The essence of digital transformation is improving energy generation and consumption by modeling and extracting insights in real time. Moreover, it involves taking information from the analog world (or the offline world) and bringing it online into the digital age to run real-time simulations and quickly respond to environmental changes. Ultimately, the end goal of digital twins—and digital transformation—is to transform legacy processes and systems, improve quality and efficiency, and reduce time, money, or energy waste.

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About The Author

Harald Remmert’s picture

Harald Remmert

Harald Remmert is CTO, Cellular Solutions, at Digi International, a leading global provider of mission- and business-critical IoT connectivity solutions. In more than 25 years of industry experience, he has held multiple leadership roles with a proven track record of introducing successful products to the market. In his current role at Digi, he is responsible for technology strategy and for driving digital transformation with new, innovative products, services, and solutions based on 5G, edge computing, machine learning, and artificial intelligence.