This module will cover the modelling and analysis of future energy systems, with a focus on renewable energy resources and how storage and network infrastructures can aid their integration into the energy system. Directly from the start of the course, students will be exposed to working with real data regarding historical weather data, land eligibility constraints, existing power plant fleets, transmission network data, electricity markets, and demand time series to learn about the challenges and solutions for a successful transition towards climate-neutral energy systems across the globe. Topics of the course include:

• Time series analysis of wind and solar generation, energy demands, technology costs and prices.
• GIS-based evaluation of renewable energy potentials.
• Modelling of daily and seasonal energy storage.
• Modelling of (linearised) power flows and transmission networks.
• Introduction to mathematical optimization (or repetition thereof).
• Electricity market designs with renewable electricity (merit order, market values, re-dispatch, nodal pricing)
• System planning of renewables deployment, energy storage and transmission infrastructure.
• Modelling of sector-coupling and demand-side management (examples from industry, buildings or transport).
• Modelling under uncertainty and methods of complexity reduction.
• Programming of energy system models in Python (e.g. pandas, geopandas, networkx, pyomo, cartopy, rasterio, PyPSA and atlite).
• Visualization and communication of energy system analysis.