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This program will focus on how mathematical modeling can help answer questions regarding the impact of green (low carbon) energy on society and the ways in which financial incentives and regulations and infrastructure changes  can enhance outcomes and accelerate the transition to a green electricity system. It will identify the ways in which mathematical tools  can inform and shape appropriate public and private investments and decisions and navigate the trade-offs encountered in moving to a more sustainable economy.

Reports from the Intergovernmental Panel on Climate Change and other national and international scientific advisory bodies are spurring governments to make announcements about net zero commitments. The transition to economies with zero carbon will require substantial investment and deployment of new technologies for providing, transporting, storing and consuming green energy. It will also require institutional changes to manage an orderly and just green energy transition. This transition is happening very slowly due to technical, socio-economic and political constraints. There is also uncertainty and complexity due to the wide range of actors shaping the energy transition and the interdependencies across sectors, infrastructures and  countries. Energy providers have been slow to increase renewable energy capacity and infrastructure at the rates required to keep global temperature rise in line with the goals of the Paris Agreement,  for a range of reasons including their institutional incentives and the changing policy and international environment. There is also increasing evidence that some of the policies and decisions that have already been made have imposed a greater burden on vulnerable and marginalized parts of society. In short, recent research across a range of disciplines has helped to understand the role and relationships across different institutions, drivers, and systems in failing to deliver the pace of change required in the energy system in a just manner and  what can be done to speed it up. However, insufficient attention has been paid to the formal application of mathematics in this setting of complex systems with multiple sources of uncertainty and variability. This program is intended to initiate the development of a core body of research that will aim to provide a systematic framework or set of frameworks for analysing some of these problems. It will bring together leading researchers who have demonstrated an interest and willingness to work at the boundary of different disciplines, but for whom face-to-face encounters are difficult to arrange due to disciplinary diversity and separation.


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Laura Diaz Anadon University of Cambridge
Michael C. Ferris University of Wisconsin-Madison
Dennice F. Gayme Johns Hopkins University
Andy Philpott University of Auckland