After successful completion of the course, students are able to develop, implement, solve and evaluate econometric models (especially those of energy demand) as well as optimization models (linear, non-linear, dynamic) according to the complexity of the problem.
04.03.2024 (Golab/Auer): Introduction to energy modelling
11.03.2024 (Auer): Introduction to econometrics and statistics
18.03.2024 (Auer/Zwickl-Bernhard): Econometric energy demand models - applied examples
08.04.2024 (Auer/Golab): Continuation - applied examples, Exercise 1
15.04.2024 (Golab): Linear optimization: theory and introduction
22.04.2024 (Golab): Introduction to source-code development (Python) incl. LP/MILP application example in energy economics, Exercise 2
29.04.2024 (Golab): Dual / primal optimization model
06.05.2024 (Golab): Application example of linear optimization in power plant dispatch planning (incl. consideration of duality), Exercise 3
13.05.2024 (Zwickl-Bernhard): Nonlinear optimization
27.05.2024 (Zwickl-Bernhard/Auer): Selected examples in energy economics - nonlinear optimzation, Exercise 4 (Part 1); Introduction to dynamic optimization
03.06.2024 No lecture
10.06.2024 (Auer): Continuation - Dynamic optimization; Selected examples in energy economics - dynamic optimzation, Exercise 4 (Part 2)
17.06.2024 (Auer/Golab): Application of dynamic optimization - theory of optimal resource depletion (fossil, renewable); Discussion/Feedback of the 4 Exercises
24.06.2024 (Golab): Written exam
The overall grade (100% of the total achievable points) consists of 2 parts:
50% of the total points can be achieved from the 4 exercises that have to be worked out and delivered during this course. The number of points per exercise can vary and will be announced at the presentation of the exercises.
50% of the total points can be achieved in the written exam at the end of the semester. This written exam consists of 5 questions (10% each), the vast majority of these questions being simple (arithmetical) examples, using the basic principles of econometrics and optimization.
IMPORTANT:
BOTH in the exercises AND in the written exam, HALF of the number of possible points must be achived in order to get a POSITIVE overall grade of this course. It is not enough to achieve a total of more than 50% of the possible total points of this course, but less than 25% in one of the two parts.
In this course great emphasis is put on understanding the basic principles in modeling in general and in econometrics and optimization in particular.
In the written exam, a non-programmable calculator is allowed, but not mandatory. The (arithmetic) examples are designed in such a way that the determination of extensive quantitative results is not in the foreground. Rounding of results is allowed / desired.
Physical attendance in this course is HIGHLY (!) recommended; not least to better understand the theoretical background/methodologies and to avoid misunderstandings in the excercise tasks and delivery rountines.
The student has to be enrolled for at least one of the studies listed below
The following documents are available for download on TUWEL:
- Script: Energy modeling and analyzes
- ppt slide set per lecture/unit
- Several necessary documents in the context of the exercises (research questions, Python files, submission)
- In general, no special knowledge is required
- Analytical thinking and willingness to learn autonomous source-code development in Python must be present
- There should be interest in interdependences in energy economics
