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Digital twins: Taking the next digital step

image credit: FuseForward

This item is part of the Advances in Utility Digitalization - Special Issue - 10/2020, click here for more

The past few years have seen the Industrial Internet of Things (IIoT) evolve from a theoretical way for operations and plants to become more efficient to a digital reality in the way utilities operate on a day-to-day basis. From equipment monitoring to smart meter applications – and everything in between – sensors, the data they produce, and the smart applications these connected systems enable, have brought numerous benefits to utilities.

These organizations are now looking at how to achieve additional advantages from their sensor-driven operations through digital twins. A virtual copy of a physical building, combining a 3-D model of a facility with the dynamic data needed to show visualizations and analysis, a digital twin provides a decision support tool that leverages real-world data to produce predictions or simulations that enable improved decision making.

A digital twin is far more than just a buzzword. For years, digital twins have been ranked among the top technology trends, and many companies – including FuseForward – are actively involved in pilot projects across a number of use cases.

A bridge between the physical and digital world

A digital twin uses the data generated by all the smart components that use sensors to analyze different scenarios to provide business and other contextual data. The ultimate evolution of the digital twin will be to create, test and build an entire operation in a virtual environment, and only when it performs optimally will the physical operation be built.

Today’s digital twins provide a vital link between the physical and virtual worlds, using existing systems and processes as well as behavioral models to simulate how people will interact with the systems they touch.

Utility 2.0

It wasn’t that long ago that smart meters were the biggest digital change in utilities, but the IIoT now encompasses everything from continuous monitoring of networks to asset visualization and analytics. Digital twins can offer predictive capabilities, using real-time IoT data (and more) to issue predictions of events long before they occur.

For example, digital twins can foresee power grid failure in utility environments by predicting specific factors like the likelihood of fires starting, or gas leaking from individual asset components, or pipes bursting. Digital twins allow utility workers to visualize an asset in the context of the system and the surrounding environment, check its status, and perform analyses and simulations. This enables utilities to better understand the past and current performance of their systems while helping them predict future performance.

Digital twins give utilities actionable insights that help them predict performance and identify failures before they happen, as well as optimizing asset performance and risk-based planning. Enabled by intelligent and connected digital infrastructure, digital twins support planning, design, construction, and operations for smart utilities.

Covid-19 and safer operations

Recently, a new, more urgent use case has emerged for digital twins—mitigating the impact of COVID-19. Digital twins provide the ideal way to ensure a smooth transition to a more remote and distributed workforce, as well as providing for safe re-entry for workers.

Visibility of a building’s inner workings has never been more important, particularly when it comes to HVAC systems. Agile, scalable, and dynamic workplaces are needed now more than ever. Digital twins support these requirements by providing the data and visualizations needed to make more rapid and flexible decisions.

One of the most pronounced impacts digital twins have had is in supporting social distancing. Virtual employee and occupant traffic pattern analyses help evaluate workflow patterns and adjust workplace designs and protocol to better manage social distancing, while also being used to support the improvement of indoor air quality in facilities by operating HVAC systems with an eye to occupancy pattern. The pandemic truly has highlighted the importance of digital twins to go beyond reliability, productivity and human experience — to create an interrelated, enhanced, resilient operation.

Getting Started

Digital twins are decision support tools. You don’t need to go all the way to the creation of a comprehensive digital twin – by focusing on using data to make better decision making you will be on the way there.

There are a few easy ways to get started. First, identify a burning area that you can use to make a decision. Is there an aspect of your operation that would benefit from improved decision making? Start small. Start structuring data, and incorporate the systems and processes required for a digital twin in the future. Once you have done this, you will be ready to launch a pilot project to validate that you are getting a return on your investment.

FuseForward can help. Get in touch with us to learn more, and get started with your first digital twin pilot project.

Mark  Damm's picture

Thank Mark for the Post!

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Discussions

Matt Chester's picture
Matt Chester on Sep 29, 2020 11:45 am GMT

There are a few easy ways to get started. First, identify a burning area that you can use to make a decision. Is there an aspect of your operation that would benefit from improved decision making? Start small. Start structuring data, and incorporate the systems and processes required for a digital twin in the future.

For entities who haven't yet embraced the possibility of the digital twin, this may be easier said than done if they aren't yet fluent in where those data insights can benefit. For those who may be behind the curve, where do you recommend they start looking for such opportunities? 

Mark  Damm's picture
Mark Damm on Oct 5, 2020 4:20 pm GMT

Digital twins sound complicated, but at a basic level they are tools that use data to support decisions. If you’re looking for opportunities to get started in this area, I would first recommend examining the existing data sources you have. Are you collecting data that is not being put to use?

 

The use of sensors and IoT devices have exploded in recent years, but less than 1% of the data generated by these devices is used. A digital twin project presents a great opportunity to make use of this data.

 

If you are looking for inspiration on potential useful applications, I would simply look to others in the industry. Whether that is keeping up with the latest news, or reaching out to your network, there is so much innovation in this area it’s only a matter of time before you’ll start identifying opportunities of your own.

Julian Jackson's picture
Julian Jackson on Oct 9, 2020 8:00 am GMT

How are digital twins going to affect the smart cities of the future? Should digital twins be designed in at the planning stage, or implemented after the city is built, or at least its major buildings are completed? How much extra computing power will we need and will the energy demands of that offset emissions savings?

Mark  Damm's picture
Mark Damm on Oct 9, 2020 10:11 pm GMT

Thanks Julian - great questions. My thoughts below:

Should digital twins be designed in at the planning stage? Or after?
 
If a city is in the design phase now and plans to develop a digital twin, then opportunities for data collection and digital twin development should definitely be a consideration during design. 
 
However, there are still plenty of opportunities to develop digital twins for established buildings and cities. For example, we are currently developing a digital twin for an existing large university campus (60+ buildings).  The campus is a mix of older buildings, along with newer digitally enabled ones. Data from newer digital buildings helps us simulate and model the older ones, so we can develop renovation plans and optimal maintenance programs. 
 
How much extra computing power? And how will energy demands offset emissions savings.
 
This is a tough one to answer as it can vary widely depending on data generated, what you are trying to achieve and the infrastructure you are using. For example, cloud computing has increased energy efficiencies over on-premise infrastructure. 
 

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