The urgency of climate change became more evident in January 2025, as new global temperature records were set [i] . Reports show that despite the cooling influence of La Niña, the critical 2°C increase could be reached by 2045. As national policies face greater scrutiny, industries - especially the energy sector- are under pressure to mitigate climate risks and transition to low-carbon solutions.

Operational research (OR) is playing a key role in shaping energy systems capable of adapting to climate change while integrating renewable energy sources. In recognition The OR Society awarded the 2024 President’s Medal to Smith Institute for its pioneering work on the Dynamic Reserve Setting (DRS) project, developed in collaboration with National Grid Electricity System Operator (ESO) to enhance the security and economy of Britain’s electricity grid.

As Dr Kieran Kalair, Principal Consultant at Smith Institute, said at the time the DRS has the potential to revolutionise how reserve setting is done for the GB electricity grid, making it more sustainable, efficient, and effective.

To delve deeper into this topic, Inside OR spoke to two experts from the University of Edinburgh, Chris Dent, Professor of Industrial Mathematics, and Dr Lars Schewe, Reader in Operational Research, who have been working on projects aimed at future-proofing the UK’s energy networks. They are focused on finding solutions to help energy systems cope with the pressures of climate change, with OR playing a role.

Addressing the Challenges of Decentralised Energy Networks

The UK’s energy grid, once centralised and dominated by large generators, has become increasingly decentralised. “We are no longer in a world with just 50 generators where someone in a control room can sit and control all of them with the press of a button,” says Schewe. With thousands of smaller units - like solar farms and wind turbines - feeding into the grid, this has introduced new complexities, especially as these units are weather-dependent.

Generating electricity without fossil fuels is not only an engineering challenge but also a significant mathematical one. “To meet the challenging target of decarbonising the electricity supply by the mid-2030s, we must accelerate research and innovation,” explains Dent.

With renewable sources being weather-dependent, Dent and Schewe stress the need for sophisticated prediction and decisionmaking tools to manage energy demand, plan for outages, and support faster decision-making. “We need more automated tools to manage the growing complexity of the system,” says Schewe. “Currently, there’s still heavy reliance on manual processes. But OR can ease the decision-making load by automating many routine tasks.”

The Optimal Outage Planning System Project

Schewe is involved in the NESO (National Energy System Operator) Optimal Outage Planning System project [iii], designed to support the transition to a net-zero energy system. Using Optimal Power Flow (OPF) models, the project generates potential scenarios to manage overloads and ensure grid stability. The goal is to optimise the UK’s energy network, particularly as renewable energy sources like wind and solar increase in prevalence, ensuring future resilience.

Outage planning is currently based on worst-case scenarios, with limited consideration for the impact of changing system conditions, such as fluctuations in generation or weather, or how one outage might influence another. This approach has traditionally relied on “rules of thumb.” With the rapid pace of change, these methods are starting to show their limitations, especially as much of the work is spent reacting to situations and re-planning.

The project aims to integrate better risk estimation into planning optimisation, making the workload more manageable for the Network Access Planning (NAP) process. “The project focuses on allowing easier network access which will allow faster construction and maintenance,” says Schewe. “It’s about making the system more flexible and responsive to the demands and conditions of a decarbonised energy system.”

Schewe highlights the need for better tools - not just for forecasting, but for enabling faster decision-making. “The bottleneck is often not data quality itself, but the decision-making process,” he explains. “Engineers still rely heavily on their judgment even in routine cases, which can slow response times. The project has demonstrated that OR can help by automating routine tasks, but human expertise will always be essential, especially in extreme situations,” he adds.

Climate Resilience and Future Challenges

Climate change is complicating energy systems, as extreme weather events like floods, wildfires, and heatwaves increasingly disrupt multiple assets. Dent, who is more involved in climate resilience projects and energy network planning, warns that current models may not be sufficient to address these risks due to data gaps. “We must account for extreme weather events, even if they haven’t been observed in the past,” he explains. “For example, large-scale forest fires or extreme heatwaves could simultaneously impact multiple assets, which current models don’t fully consider.”

Dent stresses the importance of learning from past events like the 2019 and 2022 heatwaves. “Insights from those managing the system during these events are invaluable,” he notes. “These real-world experiences can help build models to predict how the system will respond to future climate challenges.”

As the UK’s energy system becomes more interconnected with Europe, Dent highlights that managing climate-related risks will require sophisticated tools, especially as renewable energy sources grow in prominence. “We need to think about how everything fits together computationally,” Dent says. “Operational research will play a key role in managing these risks and ensuring future resilience.”

Looking Ahead: OR’s Role in the Future Energy Landscape

Dent and Schewe agree that OR will be essential for managing the growing complexity of energy networks. “In the next few decades, OR will be indispensable for predicting energy demand, integrating renewables, and maintaining grid stability,” Dent says.

Dent adds that OR will be crucial for managing the uncertainty of renewable output, especially as large-scale energy storage solutions emerge. “As the European grid becomes more interconnected OR will be vital for optimising how these systems integrate.”

Schewe, also sees OR as crucial. “The tools we develop today will help the grid adapt to future challenges,” he says.

Conclusion

OR’s expanding role in energy systems is evident in projects like DRS and NESO, which are reshaping grid management in the UK. As climate change intensifies, the need for resilient, efficient energy systems grows. OR is an invaluable tool in automating decision-making, forecasting energy trends, and ensuring grid stability. By combining advanced computational tools with human expertise, Dent, Schewe, and others are paving the way for a more sustainable and resilient energy future, ready to tackle the complex challenges posed by climate change.

References:

https://ukhealthalliance.org/news-item/ukhacc-bulletinfebruary-2025/

https://plus.maths.org/content/balancing-equations-lowcarbon-energy-network

https://www.research.ed.ac.uk/en/projects/optimaloutage-planning-system