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Iain Staffell
Researcher at Imperial College London
Publications - 136
Citations - 13782
Iain Staffell is an academic researcher from Imperial College London. The author has contributed to research in topics: Renewable energy & Electricity. The author has an hindex of 45, co-authored 121 publications receiving 8944 citations. Previous affiliations of Iain Staffell include University of Birmingham.
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The role of hydrogen and fuel cells in the global energy system
Iain Staffell,Daniel Scamman,Anthony Velazquez Abad,Paul Balcombe,Paul E. Dodds,Paul Ekins,Nilay Shah,Kate R. Ward +7 more
TL;DR: A comprehensive review of the potential role that hydrogen could play in the provision of electricity, heat, industry, transport and energy storage in a low-carbon energy system, and an assessment of the status of hydrogen in being able to fulfil that potential is presented in this article.
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Future cost and performance of water electrolysis: An expert elicitation study
TL;DR: In this paper, the authors present expert views on future capital cost, lifetime and efficiency for three electrolysis technologies: alkaline (AEC), proton exchange membrane (PEMEC) and solid oxide electrolysis cell (SOEC).
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Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data
Stefan Pfenninger,Iain Staffell +1 more
TL;DR: In this paper, the authors demonstrate how the MERRA and MERRA-2 global meteorological reanalyses as well as the Meteosat-based CM-SAF SARAH satellite dataset can be used to produce hourly PV simulations across Europe.
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Using bias-corrected reanalysis to simulate current and future wind power output
Iain Staffell,Stefan Pfenninger +1 more
TL;DR: In this article, the first international validation of reanalysis for wind energy, testing NASA's MERRA and MERRA-2 in 23 European countries, was reported, showing significant spatial bias, overestimating wind output by 50% in northwest Europe and underestimating by 30% in the Mediterranean.
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The future cost of electrical energy storage based on experience rates
TL;DR: In this paper, the authors analyze data on 11 storage technologies, constructing experience curves to project future prices, and explore feasiblity of these technologies for decarbonizing personal transport and enabling highly renewable electricity systems.