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Energy System Modelling

Summer Semester 2020, Karlsruhe Institute of Technology

Kaggle nbviewer Colab

Resources

Slides Video Topic
Lecture 1 Lecture 1 Introduction to energy system modelling
Lecture 2 Lecture 2 Consumption, Generation and Time series analysis for Germany
Lecture 3 Lecture 3 Renewables in Germany versus Europe, Balancing Energy/Capacity, Graph Theory, Linear Power Flow
Lecture 4 Lecture 4 Power flow theory and solutions
Lecture 5 Lecture 5 Storage modelling, demand-side management (briefly)
Lecture 6 Lecture 6 Optimisation, KKT conditions
Lecture 7 Lecture 7 Introduction to electricity markets
Lecture 8 Lecture 8 Optimisation and markets with networks and storage
Lecture 9 Lecture 9 Investment in dispatchable generation, screening curves, investment in transmission
Lecture 10 Lecture 10 Cost recovery from market, renewables in electricity markets, high shares of wind and solar, network versus storage optimisation
Lecture 11 Lecture 11 Discounting, net present value (NPV Jupyter notebook and as webpage), LCOE, multi-horizon investment, learning curves, path dependency (multi-horizon Jupyter notebook and as webpage)
Lecture 12 Lecture 12 Sector coupling, heat in buildings, transport, industry, synthetic fuels, open energy modelling
Lecture 13 Lecture 13 Workflow management with Snakemake, spatial resolution in optimization models, optimal power flow formulations using graph cycles
Lecture 14 Lecture 14 Principal Component Analysis (PCA) applied to the power system
Lecture 15 Lecture 15 Flow allocation of network flows to generators and consumers
Lecture 16 Lecture 16 Problems with optimization models, robustness to weather and climate change, near-optimal energy systems