Introduction

ScotRail has set an ambitious goal of achieving net-zero emissions by 2045. Significant progress has been made by running much of its electric train fleet on renewable energy. However, reducing the energy usage of stations and depots across Scotland remains a challenge. These buildings are often unique, historic, and have high energy demands, being open to the public for large parts of the day. Managing energy consumption across a diverse range of stations and depots, from Aberdeen to Clydebank, is a complex task.

The Challenge

ScotRail needed to effectively understand, manage and reduce energy consumption across its extensive network of stations and depots. Traditional methods provided limited data and insights, making it difficult to implement targeted and efficient energy-saving strategies.

The Solution

By partnering with Optimise-AI, ScotRail embarked on a transformative journey. With just a few inputs in Predict, ScotRail could immediately understand their actual energy performance across 25 stations and benchmark against comparable buildings.

This was made possible by a decade of research data from other buildings, combined with advanced technology, to create digital twins across their estate. These digital twins provide real-time tracking and optimisation features, allowing ScotRail to monitor energy consumption at every level—from entire buildings to individual rooms and systems.

Based on initial intelligence from across 25 stations, ScotRail were then able to focus on 8 stations using Optimise. This allowed further granularity in understanding energy usage across stations, zones, platforms and rooms.

Implementation

The intuitive dashboard allowed ScotRail to use the platform with little guidance. Immediately ScotRail were able to benefit from immediate recommendations and adjustments, focusing decarbonisation efforts where they’re needed most.

The system's real-time tracking capabilities enable ScotRail to test decarbonization strategies within the digital twin, demonstrate ROI, and continuously track and optimise savings.

Results

The potential savings are substantial, with reductions projected of up to 40% in the short to medium term. Poul Wend Hanson, ScotRail’s Head of Sustainability, shared his enthusiasm for the project, stating:

"The capabilities Optimise-AI provides in measuring and improving energy usage and carbon reduction position ScotRail solidly on the path to net zero."

As Optimise-AI’s system gathers more data and refines its models, it is anticipated that ScotRail will achieve even greater insights, resulting in further reductions in both carbon emissions and costs.

Conclusion

This partnership represents a significant opportunity not only for ScotRail but for the entire rail industry, showcasing the financial and environmental advantages of AI-driven solutions. By embracing cutting-edge technology, ScotRail is setting a precedent for sustainable practices and leading the way toward a greener future.