Digital Twin, a game-changing optimization technology, has arrived in the water industry. To help utilities better understand its benefits and make its adoption easier, BC Smart Utility Technology Leaders Michael Karl and Jacob Young helped launch “SWAN’s State of the Art Digital Twin Architecture to Advance the Water Industry,” the water industry’s first Digital Twin architecture standard.
A year in the making, Michael led a global panel of digital experts through the Smart Water Alliance Network (SWAN) along with co-lead Chengzi Chew to develop the new reference architecture. It will serve as a simplified base map for utilities on how to plan and implement Digital Twins.
“Digital Twin is about enabling utilities to operate with a greater level of optimization, and that optimization can happen in the capital phase or in the operational phase of asset life cycles,” Michael said.
Let’s connect physical and digital
To make adoption easier and bring clarity for utilities, the diagram above illustrates the basics of Digital Twin architecture. Here are the main components:
Bookends (Nos. 1 and 7 above): Physical System and User Experiences: Most utilities will begin on the left, applying digital to their existing physical system, and progress through the components of the architecture to the right, which culminates in the way(s) users interact with the Digital Twin through customizable visualization to facilitate real-time data-driven decisions. This user-Digital Twin intersection is portrayed in the right bookend, which shows possible user experiences, including what-if scenarios, real-time performance dashboards, augmented or virtual reality (building model or BIM model overlaid with operational data), mobile alerts, and advanced automation scenarios for operational optimizations like chemical and energy reductions.
Think of the bookends as the starting point, Physical System, and the end point, User Experiences, of a trip you are planning. The need for a Digital Twin begins with the challenge or opportunity to improve the physical system and ends with the user experience developed to meet that need. You might find that there are different routes to your destination or ways of combining those routes to get where you want to go. The Digital Twin architecture standard provides a methodical way to see those optional routes to help plan the most efficient path to your goal.
“These user experiences are really about helping utilities make informed decisions that optimize the performance and create actual results. This is all built upon a layer of security and connectedness.”
Brown and Caldwell’s National Digital Water Strategy Lead Michael Karl
Sensing and Control (No. 2 above): The first phase to build out a Digital Twin is Sensing and Control because it’s the sensors, actuators, and advanced monitoring elements that measure data critical to a physical system’s performance.
For example, take a wastewater utility that wants to digitize its pump maintenance to make the system more resilient, efficient, and cost effective. A Digital Twin of the utility’s pump system would go a long way to help achieve these goals with a user experience tailored to fit the utility’s unique needs. This Digital Twin architecture would assist the utility in determining what components of the architecture it needs to turn its physical pumps into a digital representation that performs in real time or near real time and what the best user experience would be. In the Sensing and Control Phase, the utility would need to include items such as flow rate (sensor), pressure (actuator), and power consumption information (advanced monitoring element).
Data Collection and Sources (No. 3): This phase helps you figure out what system data you already have that you would need to create the Digital Twin. It comprises widely used information systems in the water industry now, such as CMMS (Computer Maintenance Management Systems), GIS (Geographic Information Systems), CAD/BIM, and automation systems. Data collection for the pump example would also contain its location, maintenance records, and design and manufacturing specifications among other data elements.
Attributes (No. 3): The data is given context through attributes: spatial, transactional, and temporal. In the real world, for our pump example, the attributes would apply location data, manufacture information like the pump make and model, and the historical performance maintenance records of the pump.
“Having this additional context that can be applied to data is critical for the analytics within the Digital Twin itself.”
Brown and Caldwell’s National Digital Water Strategy Lead Michael Karl
Data Integration (No. 4): The ingestion and integration of the physical system data allows for all data, new and historical, to be managed and made available for the Analytical Phase. Oftentimes, analytical engines need data to be formatted and provided in a very specific way before analysis can be performed. In the case of the pump system, this phase will take that pump flow data and apply time context along with the data from the other systems and turn it into a consumable method for the analytical systems.
Analytics (No. 5): There are the two main types of analytics: Data-driven models – machine learning, artificial intelligence, and other algorithmic tools – and physics-based models – traditional, hydraulic, and biological models that can be applied in static and dynamic modes as well as in real time.
Returning to the different potential routes to get from where you are now to a Digital Twin, there are also many choices on the best approach to analytical models. This is a critical component and can only be determined once clarity on the destination is achieved with full understanding of the quality and types of available data.
Let’s assume that the utility’s goal is to use Digital Twin to increase the reliability of its equipment while reducing the time commitment of O&M staff to perform preventative and reactive maintenance. The Digital Twin would need to prioritize pump stations’ maintenance within the context of the pump locations for logistics optimization, its operational abnormalities that indicated the need for maintenance, along with its design and manufacturing details. O&M staff could view all of this data in a simple interface, such as a dashboard listing the most effective route and sequence of pump station visits, parts and tools needed for each visit, safety hazards to mitigate, and labor hours expected before leaving the utility headquarters.
Real world application
The Jordan Valley Conservancy District (JVWCD) in Utah recently completed a project that illustrates how this Digital Twin architecture serves as a guide in a utility’s journey to develop a Digital Twin. A few years ago, the Utah district, which serves over 700,000 people with a peak production capacity of 250 MGD spread over three treatment plants and 41 wells, recognized the need and value in upgrading its control system network and equipment.
From the get-go, the district was committed to maximizing the value of its investment.
“Any time I can use technology to help my employees by leveraging their skills and providing tools to make better decisions, means we can stretch our resources to do more with less. We have gotten very good at collecting mountains of data. I believe that the new SCADA will allow us to shift our focus from data collection to analysis to make better real-time and long-term decisions.”
JVWCD Assistant General Manager, O&M, Shazelle Terry
Their goal was to create a mapping interface to pull from their SCADA system, laboratory information management system (LIMS), customer complaints, and water age results from their hydraulic model and use all those inputs in an interactive interface to both troubleshoot a water quality issue and test out different responses. “What their operations manager described was the Digital Twin of their conveyance and distribution system,” Jacob said.
To meet that goal, BC replaced the SCADA system in a way that created the foundation for a Digital Twin and then established a beta visualization interface: “Using ArcGIS online, it provides an interactive map interface for anyone across the utility to go in and see SCADA data, LIMS data, and AMI data for their decision-making,” Jacob said. “With this visibility into their physical system through a digital interface, they’re able to see the operational changes that occurred to identify what was having an impact.”
That impact has only amplified since pandemic response began in early spring. JVWCD was better positioned to proactively meet COVID-19 challenges through mobilizing access to their data and other operational systems. Now, the district is progressing to applying Digital Twin to its hydraulic modeling project and integrating that data into this Digital Twin.
Other examples of how utilities are using Digital Twin include managing a natural watershed in Oregon and upgrading multiple water providers and systems in Spain. Watch the webinar (above) to learn more.
Brick by digital brick
With mass Digital Twin adoption anticipated in the next five years, prepare now by laying the foundation with your digital infrastructure. BC Blue, our unique method to smart utility implementation, can help. BC Blue services and solutions, such as Digital Twin, build upon one another at a pace that matches the organizational readiness of utilities of any size.
If implemented correctly, the near-term benefits of Digital Twins include remote operations; the ability to more accurately evaluate weather-related or climate-driven situations and prepare for them; cataloging and analyzing asset and operations health to optimize investment; and simulating what-if scenarios for training in a safe environment without risk to personnel or infrastructure. The long-term benefits include advancing and enhancing water reuse, wastewater, and drinking water systems through improved planning, continuity of service, cost savings, and capital planning.
“The main purpose of the standardized water industry reference architecture is about simplifying the planning and implementation of Digital Twin,” Michael said. “Digitally transforming all this data into its Digital Twin empowers utility personnel to proactively make the critical, big-picture decisions in real time or near real time. And that is where the efficiency and cost savings are.”