373.011 Energy Modelling and Analysis
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2024S, VU, 3.0h, 4.5EC
TUWEL

Course evaluation

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise
  • Format: Presence

Learning outcomes

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.

Subject of course

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 (Zwickl-Bernhard): Continuation - Dynamic optimization; Selected examples in energy economics - dynamic optimzation, Exercise 4 (Part 2)

10.06.2024 No lecture

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

Teaching methods

Basic principles and application of:

  • Econometric methods (regression analysis, ...)
  • Linear optimization (simplex algorithm, optimization in Python, ...)
  • Non-linear optimization (Karush-Kuhn-Tucker conditions, ...)
  • Dynamic optimization (Bellman equation with recursive function, ...)

in the form of

  • Presentation of the theoretical principles
  • Discussion with students
  • Joint working out of case studies
  • Calculation of own exercise examples
  • Written elaboration/exercises of homeworks
  • Development of own source codes in Python

Mode of examination

Written

Additional information

Die Vorbesprechung aller EEG-LVA´s findet am Mo. 4.3.2024 um 10 Uhr im EI 2 statt!

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Mon10:00 - 11:0004.03.2024EI 2 Pichelmayer HS - ETIT Vorbesprechung
Mon10:00 - 13:0004.03.2024 - 24.06.2024EI 2 Pichelmayer HS - ETIT Vorlesung
Mon10:00 - 13:0020.05.2024EI 1 Petritsch HS Vorlesung mit Übung
Energy Modelling and Analysis - Single appointments
DayDateTimeLocationDescription
Mon04.03.202410:00 - 11:00EI 2 Pichelmayer HS - ETIT Vorbesprechung
Mon04.03.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon11.03.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon18.03.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon08.04.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon15.04.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon22.04.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon29.04.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon06.05.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon13.05.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon20.05.202410:00 - 13:00EI 1 Petritsch HS Vorlesung mit Übung
Mon27.05.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon03.06.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon10.06.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon17.06.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung
Mon24.06.202410:00 - 13:00EI 2 Pichelmayer HS - ETIT Vorlesung

Examination modalities

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.

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Mon10:00 - 12:0024.06.2024 EI 2 Pichelmayer HS - ETITwritten28.02.2024 00:00 - 23.06.2024 23:59TISSSchriftliche Prüfung
Fri09:00 - 11:0027.09.2024 Gusshausstr. 25, EEG Seminarraum, CF SO 29, Kellerwritten29.06.2024 00:00 - 26.09.2024 23:59TISSSchriftliche Prüfung
Thu11:00 - 13:0023.01.2025EI 9 Hlawka HS - ETIT written28.11.2024 00:00 - 22.01.2025 23:59TISSSchriftliche Prüfung
Fri09:00 - 11:0014.03.2025 CFSO29 (Seminarraum im Keller)written05.02.2025 00:00 - 13.03.2025 23:59TISSSchriftliche Prüfung
Mon - 23.06.2025written26.02.2025 00:00 - 22.06.2025 23:59TISSSchriftliche Prüfung

Course registration

Begin End Deregistration end
01.02.2024 00:00 25.03.2024 23:59

Group Registration

GroupRegistration FromTo
Gruppe 104.03.2024 16:0025.03.2024 22:59
Gruppe 204.03.2024 16:0025.03.2024 22:59
Gruppe 304.03.2024 16:0025.03.2024 22:59
Gruppe 404.03.2024 16:0025.03.2024 22:59
Gruppe 504.03.2024 16:0025.03.2024 22:59
Gruppe 604.03.2024 16:0025.03.2024 22:59
Gruppe 704.03.2024 16:0025.03.2024 22:59
Gruppe 804.03.2024 16:0025.03.2024 22:59
Gruppe 904.03.2024 16:0025.03.2024 22:59
Gruppe 1004.03.2024 16:0025.03.2024 22:59
Gruppe 1104.03.2024 16:0025.03.2024 22:59
Gruppe 1204.03.2024 16:0025.03.2024 22:59
Gruppe 1304.03.2024 16:0025.03.2024 22:59
Gruppe 1404.03.2024 16:0025.03.2024 22:59
Gruppe 1504.03.2024 00:00
Gruppe 1609.04.2024 00:00

Curricula

Study CodeObligationSemesterPrecon.Info
066 435 Power Engineering Not specified2. Semester
066 503 Electrical Power Engineering and Sustainable Energy Systems Mandatory2. Semester
066 506 Energy Systems and Automation Technology Mandatory2. Semester
066 507 Telecommunications Mandatory elective2. Semester

Literature

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)

Previous knowledge

- 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

Language

German