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Utilities Face Challenges in Using Digital Twins

image credit: ID 137114729 © Wrightstudio |

Across industries, the use of digital twins is increasing, with good reason. These virtual copies of physical assets allow companies to model various operational scenarios without having to make changes in the real world. That includes introducing new equipment without disrupting current configurations. Such abilities help businesses become more efficient, agile, and cost-effective.

For utilities, digital twin technology can provide many benefits including maximizing asset performance, predicting power outages, and integrating distributed energy resources (DERs). Yet, integrating this technology comes with some challenges.

Questionable Accuracy

Effectiveness of a digital twin rests on the assumption that the twin is an exact copy of the physical asset. If it’s not, operational efficiency could decrease rather than increase. For example, if a crew is sent out to repair or replace a piece of equipment that isn’t actually malfunctioning, the utility has wasted time and money that could have been allotted to an actual equipment failure. More severe operational and financial failures could follow as well.

Additionally, the rigorous testing required to verify accuracy up front could itself require assigning financial and human resources that could be better used for other functions.

Insufficient Data Management

While it’s easy to conceptualize digital twins as simply 3D computer models of physical objects, the technology requires another component as well: data. According to a recent Utility Analytics Institute article, the 3D computerized representation is “layered with any relevant data gathered from the system, such as SCADA, sensor, meter, and any other IoT data that might impact it.” The more data it has, and the better the quality of that data, the more accurate analyses performed with it will be.

Yet, the quality of data can be negatively impacted with the introduction of multiple digital twins. The Utility Analytics Institute article states, “The effects of bad data on such a system can easily be staggering.” Another data challenge is the use of edge technology, which involves data collection away from central processing centers and closer to the data source (such as IoT devices in the field). Data management for edge computing is still emerging and may not yet be mature enough to provide the robust processing needed by digital twins.

Security Issues

A recent Forbes article points out the profound security implications of maintaining digital twins, explaining that, while a Boeing 777 airplane costs about $344 million, the digital twin for this asset is far more valuable because, “If you control the digital twin, you control ever 777 on (and above) the planet.” Extending this concept to utilities, hackers could use access to a digital twins of power equipment to interfere with power generation. Meanwhile, those that seek to engage in such activity are “still a long way from reaching their ultimate malevolent potential.”

Therefore, the highest levels of security for digital twins is essential at a time when utilities are already highly at risk for potential attacks.

While digital twins provide enormous potential to help utilities better manage assets, reduce costs, and serve customers, their use isn’t without problems and challenges. Understanding the possible obstacles ahead of time can help companies make smart decisions about how to implement this promising technology.

What have been your utility’s experiences and challenges with digital twins? Please share in the comments.

Karen Marcus's picture

Thank Karen for the Post!

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