‘Digital twin’ reduces Reading railway station’s energy consumption

An innovative project at Reading station has the potential to improve the station's carbon emissions and energy performance by around 20%.

In an effort to help cut the station's carbon emissions and improve its energy performance, sensors are to be installed across the station that will capture live, real-time data on the station's energy usage.

Network Rail has teamed up with Atkins and Cardiff University to develop a ‘digital twin' of the station, using Cardiff University's Computational Urban Sustainability Platform (CUSP).

Using the captured data and computer modelling, baselines have been created for the station's energy consumption and carbon emissions. CUSP then maps out ways that the station's performance can be improved through energy efficiency measures. At the same time, it explores further changes that could be made and the potential impact they could have on making additional energy savings.

This approach to understanding and improving the station's energy performance uses CUSP and the ‘digital twin' of the station to simulate its current energy usage. Using existing, historical data and modelling, a number of opportunities have been identified that could improve the station's carbon emissions and energy performance, with a predicted 20% improvement.

A number of ways to reduce energy expenditure and carbon emissions with minimal costs have been identified, including:

• Improved control of lighting, such as dimming areas of the station that are not in use.
• Turning off machinery such as escalators when not in use, or overnight when train services aren't running.

As well as collecting data from the station's sensors, passenger numbers and station-user behaviour will be recorded. This data will seek to understand how identified energy savings might impact passenger safety and experiences whilst in the station.

It is hoped that the energy and carbon savings being realised at Reading can be replicated across the rail network to support Network Rail in its commitment to reducing its carbon footprint.

Adam De Benedictis, Network Rail's Regional Energy & Carbon Manager, said: “We're delighted to be working with Atkins on this innovative project which will help us gain a better understanding of complex assets – such as Reading station – and their predicted performance, allowing us to confidently identify and deliver energy efficiency measures and ultimately manage our assets effectively.

“As an organisation, we are committed to reducing our carbon emissions and playing our part in helping combat global warming while ensuring passengers' experiences in our stations and on our railways are safe, reliable and comfortable.”

Nick Tune, Technical & Technology Director at Atkins, said: “This is an important milestone as we look to harness data and technology to improve delivery at every stage of an asset's life.

“Digital twins are the centrepiece of this shift which is giving us the information needed to not only identify opportunities to improve an asset's energy performance but to interrogate future scenarios, explore further recommendations and tell us how those interventions will work with an unprecedented degree of certainty.”