Organic networks
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| Module title: | Organic grids - Seminar on nature-inspired optimization methods for electrical grids |
| Module level, if applicable | Master's degree |
| Abbreviation, if applicable | |
| Subtitle, if applicable | |
| Courses, if applicable | |
| Semester of study: | Winter semester |
Module coordinator(s): | Prof. Dr.-Ing. Martin Braun |
Lecturer(s): | Prof. Dr.-Ing. Martin Braun and Paul Kaufmann |
| Language: German | German |
Assignment to the curriculum | Compulsory module: Specialization module: Elective module: Yes |
Teaching form/SWS: | 2 SWS: Seminar |
| Workload: | 120 h: 30 h attendance time 90 h self-study |
| Credit points: | 4 |
Recommended prerequisites: | Basics of programming, Matlab basics, knowledge of electrical networks |
Intended learning outcomes | The student can: - explain and implement the principles of nature-inspired optimization methods. - model technical tasks and solve them with the help of nature-inspired optimization algorithms. - research and use solution approaches. - implement complex tasks in Matlab/Octave. implement complex tasks in Matlab/Octave. Learning outcomes in relation to the course objectives: - Acquisition of in-depth knowledge in mathematical and scientific areas - Acquisition of in-depth knowledge in electrical engineering-specific fundamentals - Acquisition of extended and applied subject-specific fundamentals - Recognizing and classifying complex electrical engineering and interdisciplinary tasks - Confidently applying and evaluating analytical methods - Independently developing and evaluating solution methods - Familiarization with new areas of research, Conducting research and evaluating the results - In-depth and important experience in practical technical and engineering activities - Working and researching in national and international contexts |
Content: | The aim of this seminar is to acquire knowledge and skills in the areas of modeling optimization tasks and the associated solution methods through practical exercises. The thematic focus is on the design and operational management of electrical grids and nature-inspired optimization methods. In the course, small groups will implement various optimization algorithms in Matlab/Octave (e.g. genetic algorithms, evolutionary strategies, particle swarm optimization), present the solutions and compare them in a competition. |
Study/examination achievements: | Form: Literature research on nature-inspired optimization algorithms as well as preparation and short presentation (approx. 15 minutes) of an algorithm family, implementation of a method from the previously selected algorithm family, presentation of the implementation approach (approx. 15 minutes), comparison of different implementation solutions in terms of optimization performance in a competition, documentation of the implementation and logs of the project progress |
Media forms: | Projector, blackboard, paper, computer |
| Literature: | Current literature will be named in the lecture. |