By Gigi Karmous-Edwards
Digital transformation of the water sector is continuing to grow in 2019. Climate change, urban population growth, tightening regulations, aging infrastructure, and water scarcity are some of the many global challenges water utilities will be forced to address in creative and cost-effective ways. To meet these needs, utilities are deploying an array of technologies that significantly alter operations and customer engagement. Examples include cloud computing, AMI, machine learning (ML), the Internet of Things (IoT), drones, and virtual and augmented reality. The application of these technologies is helping to transform utilities from data-rich environments to increasingly knowledge-rich environments. Fundamentally, digital transformation is about using data to make informed and optimized decisions. Some believe that the development of a digital twin could be a focused goal for utility transformation.
What Is A Digital Twin?
A digital twin is a virtual or digital representation of the elements and dynamics (behavior or process) of a plant or system. If applied properly, a digital twin will influence the design, build, and operation of the system throughout its lifecycle and help optimize operation through informed insights. In other words, it is a dynamic software model (hydraulic model + ML) of the physical plant/system that pairs a live feed from the real system to the digital twin for continuous calibration.
GE’s Collin Parris refers to it as “A living model that drives outcomes.” In a more urgent tone, Thomas Kaiser of SAP notes that “digital twins are becoming a business imperative, covering the entire lifecycle of an asset or process and forming the foundation for connected products and services. Companies that fail to respond will be left behind.”
First created in 2002, digital twin technology is not new, but may seem like a new term in the water sector. Today, digital twin technology is used in all industries, ranging from manufacturing and medicine to transportation and utilities… and now the water sector.
At present, most utilities are utilizing hydraulic models for engineering and planning purposes. The models typically run in batch mode with many mathematical assumptions used as inputs. However, in order to convert to digital twin capabilities, utilities will need to migrate towards continuous real-time hydraulic models and calibrate by pairing data from real-time sensors, meters, SCADA, weather, and more, with the digital twin. The digital twin becomes an integration platform that unites data from legacy systems and new digital solutions, providing a holistic view of operations. The digital twin can be used to run “what-if” scenarios, predict and prevent failures, provide early alerts of anomalies, and conduct predictive analysis.
SWAN Digital Twin For H2O Work Group
In order to accelerate the adoption of digital twin technology, Gigi Karmous-Edwards has partnered with the SWAN (SMART Network Forum) organization to create a Digital Twin Work Group, and co-chair it. The new SWAN Digital Twin H2O Work Group will help accelerate the water sector’s adoption of Digital Twin technology by bringing together global water leaders and stakeholders from utilities, technology companies, engineering firms, government, and academia to help identify and solve relevant utility challenges. This is an ongoing group that will deliver outputs, such as best practices and a roadmap for developing and maintaining a digital twin based on agreed-upon objectives.
The Work Group is open to all interested at no cost — please join to receive updates. SWAN Members will also have the opportunity to become active members in the Work Group and collaborate to develop a common Digital Twin strategy for global water utilities. The group will celebrate its launch with a half-day workshop on May 14, one day before the SWAN’s Annual Conference. Registration is currently closed — we have reached maximum capacity. However, there will be additional workshops in the near future.
Image credit: "twin jets#14665," prof.bizzarro © 2008, used under an Attribution 2.0 Generic license: https://creativecommons.org/licenses/by/2.0/