Speaker: Dr Femke Nijsse, University of Exeter
Abstract:
Solar power has seen massive and unexpected growth over the last decade. It developed from a niche technology used by ambitious citizens to a utility-scale resource used all over the world. Net-zero plans across the globe aim for 2050 or 2060. Solar energy is the most widely available energy resource on Earth, and its economic attractiveness is improving fast in a cycle of increasing investments.
During my talk, I will discuss a data-driven technology and economic forecasting model to establish which zero carbon power sources could become dominant worldwide. The simulation models seeks to explore likely future scenarios, based on historical trends, rather than exploring “least-cost” configurations of a future clean energy system, as is usually done in energy modelling.
We find that, due to technological trajectories set in motion by past policy, a global irreversible solar tipping point may have passed where solar energy comes to dominate global electricity markets, without any additional policies directly supporting solar. Uncertainties arise, however, over grid stability in a renewables-dominated power system, the availability of sufficient finance in poorer economies and the capacity of supply chains. Policies resolving these barriers may be more effective than price instruments to accelerate the transition to clean energy.
Bio:
Dr. Femke Nijsse specializes in modelling climate, energy systems, and the economy. With a background in climate physics, they earned a Ph.D. in mathematics, focusing on multi-model comparisons and statistical techniques related to decadal variability, historical warming, and climate sensitivity. In energy research, Dr. Nijsse contributed to the Economics of Energy Innovation and System Transition project, informing energy policies in China, Brazil, India, the UK, and the EU. They improved the E3ME -FTT model’s power sector representation, using evolutionary economics for technology diffusion. Currently, they’re working on cascading tipping points across sectors and a stronger implementation of hourly supply and demand in E3ME -FTT.