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Research Areas

Designing sustainable and renewable energy systems. Designing renewable energy systems means designing systems that can deal with and even thrive on the variability of solar and wind power. In a fully sector-coupled energy system where heat and transport are partially or fully electrified and synthetic fuels replace fossil ones, different strategies to balance renewable generation are available and come with their advantages and disadvantages: from continent-spanning electricity grids, to large-scale hydrogen storage, to demand response through heat electrification. All of this requires models that depict the necessary spatial and temporal resolution. Climate change is not the only urgent global problem. The design of truly sustainable energy systems also requires examining trade-offs between the energy transition and other issues, such as land use, material requirements, ecosystem impacts, and ramifications for society. As part of efforts in this area, we develop deeper integration of our models with those from other fields, such as industrial ecology.

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Software

Renewables.ninja allows users to run simulations of the hourly power output from wind and solar power plants located anywhere in the world. I envisioned, designed, and am leading the implementation of the software. Continued development of the platform and underlying scientific models is happening in close collaboration with Iain Staffell. See www.renewables.ninja and github.com/renewables-ninja.
Calliope is an energy system modelling framework using a modern and open source Python-based toolchain. I created Calliope during my PhD and continue to lead its further development. See www.callio.pe and github.com/calliope-project/calliope.
GSEE (Global Solar Energy Estimator) is a solar energy simulation library designed for fast calculations with sensible defaults. It is developed as part of the Renewables.ninja project and is the engine behind Renewables.ninja’s solar PV simulations. See gsee.readthedocs.io and github.com/renewables-ninja/gsee.
Modelblocks is a modular system of building blocks to make the data processing for models more transparent, understandable, and easier to use, share, and collaborate on. It is open-source and model-agnostic. See www.modelblocks.org.

Talks

A selection of talks I gave: