Advanced Seminar Energy Informatics (IN0014, IN2107, IN4725)
Course 0000001016 in WS 2019/20
General Data
| Course Type | advanced seminar |
|---|---|
| Semester Weekly Hours | 2 SWS |
| Organisational Unit | Informatics 13 - Chair of Application and Middleware Systems (Prof. Mayer komm.) |
| Lecturers | |
| Dates |
Assignment to Modules
-
IN2183: CSE Seminar Scientific Computing / CSE Seminar Course Scientific Computing
This module is included in the following catalogs:- Further Modules from Other Disciplines
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | Today's electric power grids are cyber-physical systems, where information and communication technology (ICT) plays an important role in reliably operating all system components. In addition, many countries have set aggressive renewable resource integration targets. Achieving these targets requires fundamental changes to the management of the electric power grid since the output of many renewable sources, such as wind and solar generation, is highly variable: it cannot be controlled on demand, exhibits large fluctuations, and is random. Thus, instead of scheduling power supply to satisfy demand, a growing fraction of the demand will have to be managed to match variable renewable generation. In addition to traditional large scale energy storage, intrinsic energy storage on the distribution level, for instance in heat, ventilation, and air conditioning (HVAC) systems and plug-in electric vehicles (PEVs), could be leveraged to dynamically align electricity consumption with variable generation. Efforts to coordinate large populations of these kinds of distributed energy storage using information and communication technology (ICT) are often subsumed under the term “smart grid”. Building smart grids requires a deep understanding of the technical and operational characteristics of electric power systems, finding efficient solutions to new optimization problems, developing appropriate data collection and storage methods, and being able to evaluate corresponding systems using model- and data-driven simulations. In this seminar, students will be able to make own research contributions in this area. |
|---|---|
| Links |
E-Learning course (e. g. Moodle) Additional information TUMonline entry |