Utilities at all stages of digital maturity can unlock huge outcomes with digital twin technology

In its most basic form, what is a digital twin?

The idea of digital twin technology has been around for quite some time. Since NASA first pioneered the concept during the 1960s, to the technology being more widely applied in manufacturing in 2002, the technology has certainly evolved over the years. While this evolution has paved the way for massive transformation across industries, it has also led to various definitions and interpretations of what a digital twin actually is, and what it is capable of doing.

By putting it to work in the right way, digital twin technology can enable a whole new level of operational resiliency

Put simply, a digital twin is the assimilation of data and a computer model feeding into a decision support system that helps operators visualize and understand how a physical asset, process or system should be performing. For the better part of the last decade, water operators have been using the technology to help detect and diagnose anomalies, test scenarios, provide real-time decision support and predict outcomes. By expanding how digital twin data is applied, utilities can achieve a whole new level of operational resiliency.

What benefits can digital twin technology deliver?

Digital twin technology can deliver operational benefits at four levels. At its most basic level, it shows operators what is happening within an asset, process or system right now. So, while the operator has visibility into current operations, the onus is on them to take action based on what they are seeing. If we take it up a notch, the digital twin can process variables to predict an outcome, but the operator still needs to manually optimize the asset process or system based on those scenarios.

In more sophisticated applications, the digital twin can feed into a real-time decision support engine to generate multiple scenarios and provide operational recommendations to achieve set performance indicators. The operator can then choose a course of action based on those recommendations, without manual intervention. When the technology is combined with decision support systems and water expertise, the digital twin has the potential to deliver autonomous, optimized control, which then frees up operators to focus on other tasks.

How can utilities apply this technology to maximum effect?

While powerful, it’s important to remember that the digital twin is an enabling technology and not a solution – its potential is only realised in how the data are applied. In the more sophisticated applications described above, digital twin technology is coupled with advanced data science, like hydroinformatics, to deliver the decision support system. This helps utilities cut through data streams by designing algorithms that deliver the most useful information to the operator at the right time.

Can you tell us more about Hydroinformatics?

At its core, hydroinformatics is about looking at age-old problems in new ways. At Xylem, we have assembled a diverse team of experts with the broadest skillset – from software and analytics to applied civil and environmental engineering practices. Not only does that team structure allow us to see water and its associated challenges from different perspectives but it also helps our clients to do likewise. 

In making sense of data, we can help utilities leverage it to its maximum effect by developing thousands of scenarios at scale. In practice, this means using a combination of algorithms and machine learning to interpret large pools of data and turning them into actionable intelligence that utility leaders can understand and act upon. The algorithms we co-develop with utility operations teams can look at things like the energy optimization of a treatment plant or bringing real-time control strategies to reduce sewer overflows.

What role can digital twin technology play in optimizing operations?

In taking a holistic approach that leverages the power of hydroinformatics, utilities can seamlessly integrate digital twin technology into their digital ecosystem to deliver enhanced visibility and predictive capabilities. This results in dramatically improved capital and operational decision-making, which ultimately allows a utility to meet their communities’ needs reliably, affordably and sustainably.

For example, by using past data to better represent the infrastructure, the digital twin enables continuous, real-time optimization and supports accurate predictions to improve the efficiency and resilience of an asset, process, or system. Operators can also minimize downtime and optimize maintenance costs by detecting and diagnosing operational anomalies quickly and implementing a proactive maintenance or asset replacement plan.

This approach also delivers critical insights into the interrelationship of assets, so operators can troubleshoot the impact of individual asset vulnerabilities on the wider network and work out what strategy is needed to compensate. From a more practical standpoint, the digital twin as part of a decision support system also helps utilities get ahead of workforce challenges, as the data generated helps new operators pick up where their predecessors left off. This drives incremental yet invaluable improvements over time.