The OR Society’s President’s Medal

The President’s Medal recognises one outstanding applied case study each year, a project that exemplifies the power of operational research in action. Selected by the President’s Committee, it honours work that demonstrates leadership, innovation, and measurable impact through the successful implementation of OR techniques.

Entries are now open for the 2026 competition.

This award celebrates practical achievement in applied OR. To qualify, your work must have been implemented and evaluated, showing tangible benefits to an organisation or community. Submissions should represent end-to-end case studies, from problem definition and modelling through to delivery and impact.

Judging Criteria

  • Impact: Proven and quantifiable benefits from implementation
  • Innovation: Original and intellectually rigorous approaches
  • Longevity: Enduring value and lessons for wider practice
  • OR Excellence: Strong methodological foundation and clarity of process

Who Can Enter

Individuals or teams engaged in operational research across academia, industry, consultancy, or the public sector are invited to apply, provided their project has been implemented and achieved measurable results.

Deadline: 30 June 2026

Submit entries to Carol McLaughlin, Head of Professional Services: [email protected]

 
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Citation for President's Medal 2024

Using explainable AI to reduce risk and improve efficiency in GB electricity reserve
Team: National Energy System Operator (NESO) and Smith Institute

The President’s Medal has been awarded to the National Energy System Operator (NESO) and Smith Institute for their project that focused on improving energy grid stability and efficiency with Dynamic Reserve Setting (DRS). It is currently being shadow tested and has already demonstrated significant cost savings. 
To secure the British energy grid, it is vital that supply matches demand. Reserves of energy are held to ensure grid stability when forecast demands and supplies deviate from the actual values. However, holding too much energy in reserve can lead to unnecessary costs and inefficiencies. This project focuses on improving energy grid stability and efficiency with Dynamic Reserve Setting (DRS). 
NESO and Smith Institute have developed an explainable AI model that dynamically recommends reserve holdings at a 30-minute resolution based on real-time data and forecasts such as weather patterns, demand across the country, and flows of electricity between Britain and other European countries. These can be influenced by factors like major televised sporting events, heatwaves, or even just higher or lower than expected wind speed or cloud coverage. Explainable AI is key for NESO, allowing engineers to understand and trust the AI’s recommendations, ensuring they can confidently manage reserve levels in real-time.
This innovative approach replaces the previous static method, reducing the amount of unnecessary, excess reserve held while maintaining system reliability—a crucial legal requirement for NESO to avoid blackouts and damage to the grid. DRS has already demonstrated significant cost savings; for example, it reduced the amount of reserve held by 1GW over two hours, the equivalent output of two nuclear reactors. This also supports the integration of renewable energy, contributing to the UK's net-zero goals.

Past winners organisations