The technology only started regaining attention in the utilities industry a year or two ago—technically, the term has been around for over a decade—but digital twins are already gaining significant inroads among major corporations and their executives. According to consulting firm Accenture, nearly half of utility executives are now using digital twins to sharpen their operational efficiency and increase the value of predictive analytics data. A new study by Juniper Research, meanwhile, projects the digital twins market to grow by up to 35 percent annually between 2019 to 2023. While the term is applied to a variety of different simulation technologies, digital twins primarily refer to AI models of utility assets, equipment, and infrastructure. You might think of them as the digital copies of DVDs or music albums, retaining all the information and characteristics of the physical object but existing in a hard drive or on the cloud.
Using digital twins, utility companies are able to run simulations that demonstrate how their assets behave and respond in a near-infinite number of scenarios. This gives engineers and operations heads valuable information about the performance, maintenance, and longevity of their assets. In some cases, digital twins are even more sophisticated, enabling utility firms to run large-scale simulations that serve as replicas for their entire operation under specific circumstances. An example of this would be using the technology to see how an operation would change if the power generated by distributed energy resources suddenly tripled. These scenarios allow utility companies to glimpse into any number of hypothetical futures—a vital resource in an industry that is poised to utterly transform over the next decade. Here, we take a look at a few ways utilities can harness digital twins to make smarter, more informed operational decisions.
Using digital twins, utility companies are able to run simulations that demonstrate how their assets behave and respond in a near-infinite number of scenarios. This gives engineers and operations heads valuable information about the performance, maintenance, and longevity of their assets.
Take Predictive Analytics to the Next Level
Predictive analytics (PA) has fast become a powerful tool in the utilities industry. Using historical information, performance indicators, and various data points related to specific components and parts, companies can understand their gas pipelines, submersible pumps, transformers, plants, and machinery on a deeper level. PA can gauge the real-time condition of this infrastructure, guiding operations chiefs to better decisions about when parts need to be repaired or replaced.
Using historical information, performance indicators, and various data points related to specific components and parts, companies can understand their gas pipelines, submersible pumps, transformers, plants, and machinery on a deeper level.
Digital twinning is an extension and evolution of this technology. Building on all the data that predictive analytics use, DT enables utilities to create digital replicas of their equipment and assets. It can then put the replicas in various scenarios that test resilience and failure rates over time. Digital twins are, in a way, the logical endpoint of predictive analytics. They give utility companies versions of their equipment from which they can draw a limitless amount of data to spur actionable insights.
Another important factor that distinguishes digital twins from the larger world of predictive maintenance is their capacity to subject assets to specific conditions to learn how they’ll perform. Putting digital twins under unique or extreme conditions can yield novel data that predictive analytics would not be able to gather from the actual physical field assets. In this way, DT gives operational teams the chance to learn more about breakdowns, failure rates, and subsequent downtime. The technology can also shed critical light on rare but potentially catastrophic scenarios, strengthening companies’ disaster protocols and minimizing future fallout.
Test Maintenance Scenarios Without Deployment
Digital twins are more than just repositories for massive amounts of potential data, though. They’re also interactive and “hands-on” in a way that many of the utility industry’s latest technologies are not. Technicians and engineers can use the digital replicas of field assets to experiment with different maintenance situations. For example, let’s say a field team wants to learn more about the best practices for a specific gas pipeline repair. Instead of traveling out into the field—or worse, waiting for the infrastructure to break down to create a learning opportunity—techs can actually reproduce these scenarios in an office, warehouse, or plant, and then troubleshoot through how to resolve them.
From predictive maintenance and behavioral analytics to distribution automation and cloud computing, a lot of the latest technology in utilities is not felt at the level of the field service engineer (FSE). Many field service chiefs will tell you, though, that their FSEs are their most important assets. They possess the proficiency to maintain equipment, resolve complicated, time-sensitive service requests, and keep operations running smoothly by virtue of their intimate knowledge of utility infrastructure. An exciting, distinguishing feature of digital twins is how they’re actually able to help your FSEs build on those critical skillsets—instead of becoming substitutes for them. By letting technicians and engineers grapple with the digital counterparts to any pump, pipe, transformer, or valve in the field, you’re giving them a chance at growing their expertise at a much faster rate than if they only encountered those problems in the field. Employing digital twins in this way is also an excellent method for bringing up younger technicians and compensating for all the institutional knowledge that stands to be lost when older techs start retiring in the coming years. During this period, utility companies will be losing irreplaceable baby boomers who’ve been around their infrastructure for three or four decades. With digital twins, though, they’ll have a much easier time cultivating a rising generation of field professionals.
While digital twins enable utility pros to see into the future of their assets—observing how they hold up under extreme temperatures, violent storms, and many years of ongoing use—field service management (FSM) software equips companies to maximize the present. The latest, most cutting-edge FSM platforms feature several of the most important emerging technologies in the industry, including analytics reporting, cloud computing, and dynamic geomapping from multiple devices. These platforms guide field service managers toward sharper, more informed operational decisions on a daily basis, and are able to give organizations a boost no matter their level of technological immersion.
While digital twins enable utility pros to see into the future of their assets—observing how they hold up under extreme temperatures, violent storms, and many years of ongoing use—field service management (FSM) software equips companies to maximize the present.
Here’s another way to look at it: field service management software such as EnSight+ provides the same level of deep data and actionable insights into operational efficiency that digital twins yield for field infrastructure.