Digital Twinfrastructure: Delivering Maximum Value for the Water Industry

Digital Twinfrastructure: Delivering Maximum Value for the Water Industry

U.S. water and wastewater utilities are highly regulated entities whose primary goals are to meet stringent regulatory requirements for protecting public health and the environment and provide services for reasonable and fair rates. These utilities are facing increasing challenges in operating, maintaining and renewing their wet infrastructure. [By “wet infrastructure” we mean the pipes, treatment plants, storage facilities and other critical components that deliver safe drinking water to our taps and remove and treat wastewater from our homes and other buildings]. Why the challenges? Because water (water supply and wastewater collection and treatment) is a capital and energy intensive industry. According to Bluefield Research, the annual capital expenditures (CAPEX) and operating expenditures (OPEX) in the U.S. municipal water sector currently stand at $65 billion and $79 billion, respectively, and are projected to reach $72 billion and $94 billion in 2027.

In this era of heightened environmental consciousness and very tight municipal budgets, digital twinfrastructure technology can play a vital role in helping utilities optimize their operations and capital spending, reduce infrastructure inefficiencies, increase resiliency, and plan and shape a better future.

Decades of under-investment have left a legacy of decaying and tumbling wet infrastructure. A significant portion is beginning to reach the end of its useful life — making it ill-equipped to address stricter regulatory requirements and environmental standards, growing populations, increased service demands, limited water supplies, extreme weather events, and decreased state and federal grants or subsidies. The American Society of Civil Engineers’ 2017 Infrastructure Report Card scored our water and wastewater systems near-failing grades of D and D+, respectively. This critical infrastructure has been systematically underfunded, in part because raising rates is unpopular politically -- especially to a nation accustomed to low water and sewer bills. The wet infrastructure investment gap is projected to fall 73% short of needs, further contributing to increased costs for treatment, pumping and operations.?The U.S. Environmental Protection Agency believes that gap will reach more than $300 billion by 2036. Digital twinfrastructure has the potential to assist water and wastewater utilities by reducing their overall costs (TOTEX), which will help to improve and sustain their wet infrastructures and to reduce/close the financial gap.

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A digital twinfrastructure is quite simply a software representation of the wet infrastructure whose information can be used to plan optimizations that will deliver improved business outcomes. By converging the digital worlds of information technology like GIS, BIM and EAM, with operational technology like telemetry, SCADA, sensors and actuators, and engineering technology like dynamic network modeling and CFD simulation, a digital twinfrastructure becomes a high-potency digital replica of the actual physical system of operating wet infrastructure assets. Unlike traditional digital engineering simulation models, a digital twinfrastructure is able to precisely monitor asset health and performance, and timely recognize potential anomalies. It is also able to mirror and accurately simulate the operation of these assets, their surrounding environment, and how they interact in real time. This enables users to confidently test out a wide range of “what-if?” scenarios, view and compare outcomes — without disrupting daily operations — in order to optimize asset performance. The result is more accurate forward visibility and better-informed decisions.

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This interdependence also means that efficiency measures in one area have the potential to realize additional efficiencies in the others, enabling optimization across all wet infrastructure assets — from plant operations to collection and distribution networks. It also allows users to proactively identify risks, prevent potential problems in real time, develop new opportunities and inform future decisions, and even plan for the future. Reducing water main breaks and leaks; minimizing sewer overflow frequency, number and volume; and maximizing flood preparedness including the determination of safe accesses or evacuation routes as well as the anticipated time when these critical facilities will become affected are some of the many benefits utilities can realize.

By removing the silos, inefficiencies, uncertainties, errors and huge resources inherent in working with traditional digital models, a digital twinfrastructure enables improvement in effectiveness, efficiency and service and reduction in costs. It dramatically shifts management decision making and expands wet infrastructure management across the entire infrastructure lifecycle, enabling utilities to optimize operations, design cost-effective maintenance strategies, better manage risk and limited budgets, identify efficiencies to generate additional revenue, increase collaboration, improve customer service and extend their wet infrastructure lifespans.

Keeping an eye out for advancements in this emerging software technology is smart, if not downright essential. The utilities that embrace it first will have a vital head start in closing their wet infrastructure spending shortfalls. It might just be a critical game-changer.

Vivek Chaudhuri

Global Commercial Growth Head | Digital Marketing, Marketing Operations, Analytics, and Marketing Technology

5 年

Great food for thought article Paul - Thanks! Bargava Subramanian - You’ve gotta read this for both addressing relevant opportunities with both data driven insights and data security (IOT).

Paloma B.

Prof. Dr. Ingeniero Civil - Digitalización y Optimización del Ciclo del Agua

5 年

Very good explanation. I have been explaining the concept of (Hydraulic) Digital Twin as well in specialised symposiums and surprisingly, nobody was familiar with the concept.?

Sachin Bhosle

Energy optimization and IBMS engineering solutions provider

5 年

great

Richard Beck

Co-founding Director at DIGATEX

5 年

Paul - good article. The real challenge is how to extract data from the existing set of drawings and documents in order to create the digital model. Would be good to talk as we use an artificial intelligence approach which has been proven on very large assets in the Oil and Gas and Mining sectors.

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Chi Chung Leung

Senior Electrical and Mechanical Engineer at WSD

5 年

Virtual Model (3D platform)?may be BIM + GIS, Data Acquisition (Sensors)?may be 5G +?IOT, Data?Analytics (Brain)?may be Machine Learning,?may be overseeing the?entire lifecycle of the physical assets with or without human intervention

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