Course details

Programming Skills in Energy Engineering

Teaching: Completely taught in English

ECTS: 3

Level: Undergraduate

Semester: Summer

Prerequisites:

Load:

Lectures	Exercises	Laboratory exercises	Project laboratory	Physical education excercises	Field exercises	Seminar	Design exercises	Practicum
0		0	30	0	0	15	0	0

Course objectives:

Introducing students to the main programming packages in energy and environment fields and their application for solving simple engineering problems.

Student responsibilities:

Class attendance, consultations and preparation of planned tasks.

Grading and evaluation of student work over the course of instruction and at a final exam:

Upon successful completion of the course, students will be able to (learning outcomes):

1 . Outline the algorithm for a complex mathematical problem and develop a flowchart as a basis for the code.

2 . Apply a programming language for the numerical solution of simple partial differential equations and solution visualization.

3 . Choose appropriate numerical method and software tools for specific engineering problems.

4 . Explain the problem of energy and mass balances during energy transformations.

5 . Using a programming language, numerically solve and display energy flows to meet different final consumption needs.

Lectures

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Exercises

1. Exercises: Introduction. An overview of the most important computer packages and their application in energy.

2. Exercises: Application of selected numerical algorithms to elementary problems in energy I.

3. Exercises: Application of selected numerical algorithms to elementary problems in energy II.

4. Exercises: Energy and material evaluation of waste materials in a sustainable society.

5. Exercises: Processing of experimental results on the example of adsorption of pollutants.

6. Exercises: Numerical solution of the 2D heat equation in Python I - finite difference method, domain and equation system definition.

7. Exercises: Numerical solution of the 2D heat equation in Python II - solution of the linear system, solution visualisation.

8. Exercises: Calculating wind turbine energy production from weather forecast in Python.

9. Exercises: DeSOx process - mass and energy balance.

10. Exercises: Material and energy analysis of different energy transformation technologies to meet the final need.

11. Seminar: Numerical analysis and presentation of heating decarbonization results in Python.

12. Seminar: Numerical analysis and presentation of traffic decarbonization results in Python.

13. Seminar: Heat storage charging simulation in Matlab and Python.

14. Seminar: Wind park operation analysis in different wind conditions and data plotting in Matlab.

15. Presentation and defence of student projects

Compulsory literature:

Recommended literature: