Iain Staffell
A multi-disciplinary scientist and research leader in physics, economics, engineering, programming and data analytics; with a drive for sustainable energy technologies.
My research interests span across energy systems modelling (simulating renewable resources, power system dispatch, demand projection), economics (market design, investment and financial modelling), and engineering (field demonstrations, custom data acquisition, life cycle assessment); and covers electricity generation (nuclear, wind, solar, conventional fossil, CCS), low-carbon heating (heat pumps, CHP), power systems (HVDC, batteries, thermal storage), and sustainable transport (hydrogen and electric vehicles).
My research interests span across energy systems modelling (simulating renewable resources, power system dispatch, demand projection), economics (market design, investment and financial modelling), and engineering (field demonstrations, custom data acquisition, life cycle assessment); and covers electricity generation (nuclear, wind, solar, conventional fossil, CCS), low-carbon heating (heat pumps, CHP), power systems (HVDC, batteries, thermal storage), and sustainable transport (hydrogen and electric vehicles).
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Papers by Iain Staffell
While EV flexibility is widely discussed, there is uncertainty surrounding the magnitude to which EVs could help electricity systems, and a distinct lack of quantitative evidence around adoption, charging behaviour and technical capabilities for load shifting. This study employs the rapid evidence assessment method to synthesise recent information. We find that studies expect that EVs could provide 1–11 GW of flexible capacity per million vehicles (median: 3.7 GW), with the ability to shift demand by 1.5–5 h (median: 4 h) and a price elasticity of –0.77 to –0.10 (median: –0.15). Diurnal profiles of charging demand and availability for providing flexibility are aggregated across multiple studies. The results are relevant for energy modellers and show that the interaction between EVs and electricity systems can be generalised on a widely-applicable basis.
using proton exchange membrane electrolysis (PEMEL), and € 10.49/kgH2 using alkaline electrolysis (AEL), € 10.88/kgH2 with grid electricity to backup the offshore wind power. A stochastic Monte-Carlo model is used to asses the uncertainty on costs and identify the cost of capital, electrolyser and wind farm capital costs, and cost of electricity as the most important drivers of LCOH across the different scenarios. Reducing the capital cost to comparative levels observed on today’s wind farms alone, could see AEL LCOH fall to € 5.32/kgH2, near competitive with conventional generation methods.
and opportunities for the workforce with important implications for just
transitions. Studies of these distributional labour impacts could benefit
from tighter linkages between energy and employment modelling. Here, we
couple a power-sector optimization model, an employment impact model
and demographic databases to understand state-level job characteristics
and the societal implications of low-carbon transitions in the US. Although
decarbonization brings consistent job growth, it heightens the need for
investment in human capital and supply chain restructuring. Major fossil
fuel-producing states need to prepare for fewer mining jobs under the US
Long-Term Strategy, so other opportunities should be created or seized.
The lowest-skilled workers will experience more uncertain employment
outcomes. Expanding renewable energy could improve opportunities
for women in fossil fuel-dependent states, but not enough to disrupt
the national gender status quo. This work provides a new quantitative
perspective to inform proactive just transition policies.
While EV flexibility is widely discussed, there is uncertainty surrounding the magnitude to which EVs could help electricity systems, and a distinct lack of quantitative evidence around adoption, charging behaviour and technical capabilities for load shifting. This study employs the rapid evidence assessment method to synthesise recent information. We find that studies expect that EVs could provide 1–11 GW of flexible capacity per million vehicles (median: 3.7 GW), with the ability to shift demand by 1.5–5 h (median: 4 h) and a price elasticity of –0.77 to –0.10 (median: –0.15). Diurnal profiles of charging demand and availability for providing flexibility are aggregated across multiple studies. The results are relevant for energy modellers and show that the interaction between EVs and electricity systems can be generalised on a widely-applicable basis.
using proton exchange membrane electrolysis (PEMEL), and € 10.49/kgH2 using alkaline electrolysis (AEL), € 10.88/kgH2 with grid electricity to backup the offshore wind power. A stochastic Monte-Carlo model is used to asses the uncertainty on costs and identify the cost of capital, electrolyser and wind farm capital costs, and cost of electricity as the most important drivers of LCOH across the different scenarios. Reducing the capital cost to comparative levels observed on today’s wind farms alone, could see AEL LCOH fall to € 5.32/kgH2, near competitive with conventional generation methods.
and opportunities for the workforce with important implications for just
transitions. Studies of these distributional labour impacts could benefit
from tighter linkages between energy and employment modelling. Here, we
couple a power-sector optimization model, an employment impact model
and demographic databases to understand state-level job characteristics
and the societal implications of low-carbon transitions in the US. Although
decarbonization brings consistent job growth, it heightens the need for
investment in human capital and supply chain restructuring. Major fossil
fuel-producing states need to prepare for fewer mining jobs under the US
Long-Term Strategy, so other opportunities should be created or seized.
The lowest-skilled workers will experience more uncertain employment
outcomes. Expanding renewable energy could improve opportunities
for women in fossil fuel-dependent states, but not enough to disrupt
the national gender status quo. This work provides a new quantitative
perspective to inform proactive just transition policies.