Advancing Energy System Modelling for Optimised Hydrogen Infrastructure and Energy Resilience in Scotland

Summary

The proposed research will advance energy system modelling to support Scotland's evolving hydrogen infrastructure needs, enhancing analytical and decision-support capabilities for complex hydrogen infrastructure projects. This PhD project aims to develop tools that can optimise site selection, enable production scaling, and provide alignment with policy-driven hydrogen objectives, such as those outlined in Scotland’s Hydrogen Action Plan.

The PhD project will be supported by existing RGU energy system modelling (ESM) frameworks and focus on four key research topics :

• Advanced Predictive Modelling: Expanding EMSs to simulate grid scenarios over extended planning horizons, helping assess the impact of increased hydrogen production on grid resilience, resource utilisation, and infrastructure investment.
• Optimisation for Multi-Vector Energy Systems: Leveraging machine learning, the modelling tool will provide precise location recommendations for hydrogen hubs based on factors such as energy availability, storage capacity, and logistics, while accounting for future energy demands and emerging renewable sources.
• Scenario-Based Decision Support: By enabling the automated exploration of alternative scenarios, the modelling approach will offer flexibility to government agencies, energy developers, and regional planners. The goal is to enable the alignment of hydrogen projects with spatial planning goals, optimising location, cost, and grid connectivity in accordance with National Planning Framework 4.
• Integration of Regulatory and Economic Factors: The incorporation of legislative and economic constraints specific to hydrogen development will make the modelling framework a valuable resource for risk management and informed investment decisions.

The resulting enhanced energy system modelling approach will support Scotland’s energy transition, enabling scalable, cost-effective hydrogen infrastructure that aligns with national objectives. In addition to strengthening Scotland's hydrogen economy, this PhD will offer adaptability to broader applications, providing useful insights for scaling hydrogen projects on a global scale.

This project is multidisciplinary, bridging engineering and computer science, making it ideal for graduates from these or related fields. The ideal candidate should have foundational coding skills, with experience in Python preferred, though Java or other object-oriented programming languages are also acceptable. Familiarity with modelling tools such as MATLAB, Calliope, or other energy system modelling frameworks is advantageous. While knowledge of hydrogen infrastructure is a plus, it is not essential, as training in AI and machine learning techniques - including single and multi-objective optimisation and time series modelling - will be provided throughout the project.

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