Ruaridh Macdonald
Research Scientist at the MIT Energy Initiative
I’m a research scientist at the MIT Energy Initiative, where I am the Energy Systems Research Lead. My research is focused on improving energy system modelling tools to better support decision-making in infrastructure planning, R&D decisions and policy design. My recent work has looked at how best to compress model inputs to allow for decades of weather and demand data to be considered, incorporate important nonlinear details in technology representations, co-optimize multi-sector models, and decompose models so that they can be solved on large computing clusters. I use these tools to answer contemporary energy questions, particularly around grid reliability, intersectoral coupling, and the role of emerging technologies.
I am a co-lead developer of the MacroEnergy, GenX, Dolphyn, and Navi tools.
I’m originally from the UK & completed my PhD in Nuclear Science & Engineering at MIT.
Selected publications
- Dynamic optimization of proton exchange membrane water electrolyzers considering usage-based degradationAIChE Journal, 2025
- Sectoral and spatial decomposition methods for multi-sector capacity expansion modelsarXiv preprint arXiv:2504.08503, 2025
- A decomposition algorithm using multiple linear approximations to solve integrated design and scheduling optimization frameworks-case study of nuclear based co-production of electricity and hydrogenComputers & Chemical Engineering, 2025
- Techno-economic analysis of decarbonized backup power systems using scenario-based stochastic optimizationEnergies, 2025
- The Competitive Space for Thermal Energy Storage on Decarbonizing GridsIn Energy Solutions for a Sustainable and Inclusive Future, 46th IAEE International Conference, June 15-18, 2025, 2025
- MacroEnergy. jl: A large-scale multi-sector energy system frameworkarXiv preprint arXiv:2510.21943, 2025
- Improved formulation for long-duration storage in capacity expansion models using representative periodsarXiv preprint arXiv:2409.19079, 2024
- Effects of charging and discharging capabilities on trade-offs between model accuracy and computational efficiency in pumped thermal electricity storagearXiv preprint arXiv:2411.07805, 2024
- Integrated Design and Scheduling Optimization of Multi-product processes - case study of Nuclear-Based Hydrogen and Electricity Co-ProductionSystems and Control Transactions, 2024
- UO2-fueled microreactors: Near-term solutions to emerging marketsNuclear Engineering and Design, 2023
- Physical cryptographic verification of nuclear warheadsProceedings of the National Academy of Sciences, 2016