inf516 - Distributed Operation in Digitalised Energy Systems (Complete module description)

Module label	Distributed Operation in Digitalised Energy Systems
Module code	inf516
Credit points	6.0 KP
Workload	180 h
Institute directory	Department of Computing Science
Applicability of the module	Master's Programme Computing Science (Master) > Angewandte Informatik Master's programme Digitalised Energy Systems (Master) > Digitalised Energy System Automation, Control and Optimisation
Responsible persons	Nieße, Astrid (module responsibility) Lehrenden, Die im Modul (authorised to take exams)
Prerequisites	Fundamentals of Optimization, Fundamentals of Digitized Energy Systems
Skills to be acquired in this module	After successful completion of this course, the students are able to analyze an application problem in cyber-physical energy systems to decide whether a distributed optimization approach could be usefully applied. Fundamentals of self-organizing systems are understood and can be transferred to specific applications. Furthermore, the basic concepts of distributed methods can be applied safely and transferred to an application case. Professional competence The students: will be familiar with the basic concepts of distributed optimization and agent systems mentioned above Methological competence The students: will be able to present the fundamental concepts of distributed optimization and agent systems mentioned above and apply them to applicationproblems in CPES Social competence The students: create solutions in small teams present and discuss their solutions reflect the solutions of others in a constructive manner Self competence The students: critically questionthe application of learned methods to a real-world problem
Module contents	In this course, fundamentals of agent-based control with applications in cyber-physical power systems are reviewed, discussed, and reinforced in the accompanying programming exercise. These are: Multi-agent systems Foundations and definitions MAS architectures Agent communication cooperative and competetive agents MAS learning in MAS Distributed Optimization CASIMIR Overview on distributed optimization CSP and COP Distributed SCP und COP Self-organizing energy systems Applications Virtual Power Plants QEMS and Microgrids DSM and DR Energy market applications Swarms for storage management Multi-purpose examples Programming part Agent framework mango Co-simulation framework mosaik Power grid simulation pandapower
Recommended reading	Yoav Shoham und Kevin Leyton-Brown Multiagent Systems: Algorithmic, Game- Theoretic, and Logical Foundations New York: Cambridge University Press, 2008, ISBN: 9780521899437 Michael Wooldridge An introduction to multiagent systems Wiley, 2009, ISBN: 0470519460 3. Russell und Peter Norvig Artificial intelligence : a modern approach Boston Pearson, 2018, ISBN: 0134610997; Nancy Ann Lynch Distributed algorithms Kaufmann, 2003, ISBN: 1558603484
Links
Language of instruction	English
Duration (semesters)	1 Semester
Module frequency	every winter term
Module capacity	50
Teaching/Learning method	V+Ü
Previous knowledge	Grundlagen der Optimierung, Grundlagen Digitalisierter Energiesysteme

Type of course	SWS	Frequency	Workload of compulsory attendance
Lecture	2	WiSe	28
Exercises	2	WiSe	28
Total module attendance time			56 h

Examination	Prüfungszeiten	Type of examination
Final exam of module	In the current semester and at the end of the event	Portfolio or oral exam or written exam