How digital twin technology can help water utilities ride the digital wave
The UN 2023 Water Conference once again highlighted the essential role of smart technologies in increasing water security. For many utilities, digital solutions are already playing a significant part in tackling complex challenges and transforming operations.
Later this month, Xylem will launch “Ripple Effect: A Movement Towards Digital Transformation” – a new paper drawing on insights from global utility leaders and experts. How did they start their digital journey? And how did they scale? This paper charts their course and provides a playbook to replicate their success.
Here, Michele Samuels, Global Practice Manager of Asset Performance at Xylem, shares her perspective on how utilities can leverage digital twin technology to make incremental improvements and move from ripple to wave.
While conversations around the digitalization of the water sector have been bubbling for the better part of this century, it is only within the last decade or so that utilities have departed from the status quo. Advances in technology, such as digital twins, are enabling breakthrough solutions, and delivering transformative outcomes for communities.
At a basic level, a digital twin is a digital representation of a counterpart in the real world. Within water utilities, this can mean the assimilation of data and an operational model that helps operators understand how a physical asset, process or system should be performing, and provide insights and predict performance under changing conditions.
Every innovation comes with a learning curve, and the clay is still wet on many of the frameworks needed to integrate digital technologies across utility operations. For some utilities, digital twin technology is powering a whole new level of operational resiliency. For others, it may not be going the distance to deliver data-led insights and decision intelligence. Ultimately, the digital twin is an enabling technology – not a solution. So how can utilities unlock its real value?
From data to decision intelligence
Traditional models for simulating infrastructure can be costly to build and don’t readily assimilate live data. Now, sophisticated machine learning tools can better represent the infrastructure by automatically calibrating to match historical data. This technology can be applied at four levels:
1. Visibility. At its most basic level, a digital twin shows operators what is happening within an asset, process, or system right now. This application relies on the operator to act based on visibility of current operations.
2. Scenarios. At this level, the digital twin is capable of processing variables to predict an outcome, but it still requires the operator to manually optimize the asset, process, or system.
3. Recommendations. In more sophisticated applications, the digital twin generates multiple scenarios and provides operational recommendations to achieve set KPIs. The operator then chooses a course of action based on these recommendations.
4. Control. When combined with decision support systems and water expertise, the digital twin has the potential to deliver autonomous, optimized control, freeing up operators to focus on other tasks.
In more sophisticated applications, the digital twin is coupled with advanced data science and water system expertise to create a powerful decision support system. By combining hydraulic modelling with expertise from traditional civil and environmental engineering, hydroinformatics engineers help utilities cut through the data by designing algorithms and interfaces that deliver the most useful information to the operator in the right way, at the right time – every time.
This sets utilities up to meet their communities’ needs reliably, affordably, and sustainably.
Supercharging through data
Utilities have a wealth of data at their fingertips. Whether at the asset, process or system level, utilities can unlock big results quickly by putting that data to work. As the utilities consulted for the “Ripple Effect” paper demonstrate, an approach of catalog, evaluate, and prioritize can provide the building blocks needed.
- Catalog the real-time data currently available and determine areas where more detailed data can support operational and planning decisions.
- Evaluate how digital technology solutions can add value through a pilot project – a low-cost route for utilities to determine the challenges, opportunities, and potential return on investment of digital technology.
- Prioritize projects aligned to the problem you are trying to solve.
Whether it’s a single bold step forward, or smaller incremental improvements over time, every move on the digital journey brings the industry closer to achieving one common goal: building a more resilient, sustainable, and equitable water future for all. By sharing best practice from the pacesetters, utilities at all stages of digital maturity can scale their transition to smart, resilient infrastructure.