In their report ‘A new perspective on decarbonising the global energy system’, published in April this year, Doyne Farmer, Matthew Ives and Rupert Way drew on over a decade of research on probabilistic cost forecasting methods shown to make reliable predictions when empirically tested on more than 50 technologies.
These methods are employed to estimate future energy system costs which show that, compared to a fossil-fuel-based system, a rapid green energy transition will likely result in overall net savings of many trillions of dollars.
In this presentation, they will discuss their research and explain why their conclusions differ so radically from most energy-economics models, and how the decades-long increase renewable energy technologies deployment have consistently coincided with steep declines in their costs. Further, they will demonstrate that if solar photovoltaics, wind, batteries and hydrogen electrolyzers continue to follow their current exponentially increasing deployment trends for another decade, a near-net-zero emissions energy system is achievable within twenty-five years. Finally, the discussion will look at the potential of these findings for policy action and their implications for the goals of the Paris Agreement.
Please note that in person attendance for this event is now full. To participate online, please register here: A new perspective on decarbonising the global energy system
This event is organised by Oxford Energy, with the Oxford Martin School Programmes on the Post-Carbon Transition, Integrating Renewable Energy and the Future of Cooling
Baillie Gifford Professor of Mathematics
J. Doyne Farmer is Director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School, Baillie Gifford Professor in the Mathematical Institute at the University of Oxford and an External Professor at the Santa Fe Institute.
His current research is in economics, including agent-based modeling, financial instability and technological progress. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to the United Bank of Switzerland in 2006. His past research includes complex systems, dynamical systems theory, time series analysis and theoretical biology.
Senior Research Officer, INET
Matthew is an economist and complex systems modeller currently working on the Oxford Martin School Programme for Post-Carbon Transition. This cutting-edge programme is focussed on positive solutions to climate change through the identification of sensitive intervention points designed to help bring about the rapid reductions in global emissions necessary to meet our Paris Agreement obligations.
Postdoctoral Research Officer, INET
Rupert has a PhD in mathematics and is interested in the physics and economics of networks, learning and systems engineering, especially in relation to energy systems and sustainability.
He now works on innovation forecasting, technology networks and operations research, in particular looking at path-dependence, risk and diversity in RD&D programs.
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