Digital twin tech could help slash ‘phantom load’ waste

Adopting digital twin technology to manage the power consumption of idle devices could save organisations thousands of pounds a year and help reduce their carbon footprint, new research suggests.
 
Engineers from the University of Glasgow’s James Watt School of Engineering have developed a prototype of a digital tool which can monitor and manage ‘phantom load’ - the electricity consumed by devices like computers or office equipment when they are plugged into mains power but are not in active use.
 
Previous research has shown that up to a third of the electricity used in office buildings can be accounted for by phantom power. The research team set out to use their expertise in digital twin technology to develop a more intelligent, behaviour-adaptive approach to managing the phantom load.
 
Digital twins are dynamic, data-driven virtual models designed to represent complex adaptive systems. Using smart sensors, they continuously capture real-world data on variables such as electricity use, enabling real-time insights and predictive capabilities.

The team’s system draws data from a network of smart energy sensors, which send information on electricity to a central server using the LoRaWAN protocol, a widely-used standard in ‘Internet of Things’ systems.
 
The server uses sophisticated fuzzy-logic algorithms to identify power usage patterns, and can identify when a device is actively being used, and when it's drawing phantom power.
 
When the system detects prolonged idle periods, it sends users a prompt on their screen to determine if they're conducting remote work or running background processes.
 
This approach aims to raise user’s awareness of their device’s idle periods, perhaps encouraging them to make more careful use of their devices, while also preventing legitimate work processes from being cut off. If users don't respond, or confirm the device isn't needed, the system can automatically switch off the equipment, cutting off its phantom load altogether. The system can also draw the data it gathers to make predictions about the likely electricity consumption of devices for the next day.
 
The team’s research is set to be presented as a paper at the IEEE’s international GLOBECOM conference next week.

Dr Ahmad Taha, of the University of Glasgow’s James Watt School of Engineering, is leading the work with his team Yuwen Wang, Zhihong Xu, and Shilong Yan. He said: " I'm a firm believer in the idea that that small, collective actions on climate issues can have big effects, and phantom power use is an obvious candidate for that kind of action. The edge-enabled digital twin system we’ve developed is designed to help organisations reduce their power waste in two different ways.
 
“Firstly, it can help identify power management efficiencies in real time, cutting power consumption and reducing carbon emissions. Secondly, by reducing devices’ use of electricity, it could help reduce the need to replace older devices with newer, more power-efficient ones. That in turn could help organisations save on equipment costs in an increasingly challenging economic environment.”
 
The team validated the potential of the tool by applying it to a lab at the University of Glasgow which is home to workstations connected to 30+ power-drawing devices.
 
The paper shows that using the tool in the lab reduced the total power consumption of the workstations by around 40% each week by carefully managing their electricity use. The team estimate that the tool, which uses 27 rules to optimise its decision-making, could reduce total phantom load by 82%, saving the University around £9,000 in electricity costs every year if used full-time across the university.
 
Dr Taha added: “This is a really encouraging result, even applied to a small fraction of the devices around the University’s campus. It suggests that there could be huge savings to be found by applying digital twin technology to help tackle the phantom power problem.
 
“Reaching net zero will require a broad-spectrum approach to energy monitoring, and this tool could be a valuable part of wider institutional approaches to minimising their carbon footprint using digital twins to monitor variables like occupancy and temperature control. We’re working to investigate how this tool could play a role in the University’s wider efforts to achieve net-zero by 2030, and we’re keen to explore in parallel how it could be used in other universities, businesses and even in homes in the years to come.”
 
Yuwen Wang, Zhizong Xu, Shilong Yan, Professor Muhammad Ali Imran and Professor David Flynn of the James Watt School of Engineering co-authored the paper. The team’s paper, titled ‘Edge-Enabled Digital Twin System with Fuzzy Logic for Energy Optimization in the Built Environment’, will be presented at the 2025 IEEE Global Communications Conference (GLOBECOM) in Taipei, Taiwan on Monday 8th December.