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Seminar: Energy Informatics (IN0014, IN2107, IN4725)
Advanced Seminar Energy Informatics (IN0014, IN2107, IN4725)

Lehrveranstaltung 0000001016 im WS 2019/20

Basisdaten

LV-Art Hauptseminar
Umfang 2 SWS
betreuende Organisation Informatik 13 - Lehrstuhl für Anwendungs- und Middlewaresysteme (Prof. Mayer komm.)
Dozent(inn)en
Termine

Zuordnung zu Modulen

weitere Informationen

Lehrveranstaltungen sind neben Prüfungen Bausteine von Modulen. Beachten Sie daher, dass Sie Informationen zu den Lehrinhalten und insbesondere zu Prüfungs- und Studienleistungen in der Regel nur auf Modulebene erhalten können (siehe Abschnitt "Zuordnung zu Modulen" oben).

ergänzende Hinweise 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. Smart buildings are not just expected to be energy efficient, but at the same time able to control demand and deliver distributed clean energy. 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 to this research area.
Links E-Learning-Kurs (z. B. Moodle)
Zusatzinformationen
TUMonline-Eintrag
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