This lecture will introduce several open-source frameworks for modelling the energy system and assessing the transition to renewable sources in the context of climate change mitigation and sustainable development. We will discuss the role of quantitative, model-based pathways in international and national climate mitigation policy, in particular the reports by the Intergovernmental Panel on Climate Change (IPCC), and the students will learn how to develop scenarios of the energy transition using open-source tools and readily available data.
Publicly available course material
The lecture slides will be made available on data.ene.iiasa.ac.at/teaching/ under a Creative Commons CC-BY 4.0 International License.
Lecture 1
We will discuss the principles of open-source and collaborative scientific programming for energy modelling. Concepts include version control using GitHub, the principles of code review, unit tests and continuous integration.
Lecture 2
Integrated assessment models are a key tool for developing narratives and quantifying pathways to understand system transitions and impacts of policy measures. We will discuss different model types which can be used in this area, and we will review the role of numerical modelling of human and earth systems for policy-makers in the context of the IPCC reports and other global outlooks.
Lecture 3
We will use the pyam package, a Python package for visualizing and analyzing integrated assessment scenarios, for understanding climate change mitigation pathways used in the IPCC Special Report on Global Warming of 1.5°C (SR15).
Lecture 4
We will turn to developing a national-scale energy system model using the open-source MESSAGEix Integrated Assessment Modeling Framework. After working through an example, students will implement a stylized model for another country and analyze different climate change mitigation policies.
Lecture 5
We will discuss how to extend the stylized national energy system model developed in lecture 4 into an integrated assessment model by including land use and agriculture, water use, and other aspects of sustainable development.
Attention: An introduction into several lectures at EEG takes place on 4th March 2019 (10 am) at EI2!
Start of this lecture (blocked): Tuesday, 26.03.2019, 14:00-17:00 (Lecture Hall: Dekanatszimmer CFZ217, GH 25, Stg. 7, intermediate floor between 2nd and 3rd floor)
Schedule of Lectures (several of them in Lecture Hall: Dekanatszimmer CFZ217, GH 25, Stg. 7, intermediate floor between 2nd and 3rd floor):
The grades will be based on two homework assignments from lectures 3 and 4, as well as an oral discussion of the submitted assignments at the end of the course.
Software resources
anaconda (Python and Jupyter installation framework) - www.anaconda.com
pyam documentation - software.ene.iiasa.ac.at/pyam
MESSAGEix framework - MESSAGEix.ene.ac.at
Resources for the IPCC Special Report on Global Warming of 1.5°C (SR15)
Full report - www.ipcc.ch/report/sr15/ (see Chapter 2 in particular)
Scenario Explorer - data.ene.iiasa.ac.at/iamc-1.5c-explorer
Assessment notebooks
Scientific literature
MESSAGEix framework documentation
Daniel Huppmann, Matthew Gidden, Oliver Fricko, Peter Kolp, Clara Orthofer, Michael Pimmer, Adriano Vinca, Alessio Mastrucci, Keywan Riahi, and Volker Krey. The MESSAGEix Integrated Assessment Model and the ix modeling platform. 2018, submitted. Electronic pre-print available at pure.iiasa.ac.at/15157/.
Students are expected to have a good understanding of the energy system and the policy questions concerning climate change mitigation and the transition to renewable energy sources. PhD students with an interest in numerical modelling and analytical methods are encouraged to join.
The frameworks used during the lectures and assignments are based on Jupyter Notebooks and Python. In-depth knowledge of Python is not required, but prior experience with at least one scientific programming language (Python, Julia, R, Matlab, Java, C, etc.) is expected.
Students that have not previously worked with Python should install the latest release from www.anaconda.com (Python 3.7 or higher) before the first lecture. Basic understanding of Python and learning to work with pandas DataFrames is highly recommended, see https://pandas.pydata.org/pandas-docs/stable/10min.html.
Running the MESSAGEix framework requires a working installation of GAMS (www.gams.com), but knowledge of GAMS as a mathematical programming language is not required. The MESSAGEix tutorials can be run via Jupyter/Python notebooks without a GAMS license file as preparation prior to the lectures, but developing larger models (e.g., extending the time horizon, adding technologies, disaggregating the demand sector) requires a valid GAMS license. Note that the license which can be purchased via TU Wien does not include the powerful solvers CPLEX and GUROBI. A course license valid for several weeks will be provided prior to the third lecture.
