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

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

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Module label Distributed Operation in Digitalised Energy Systems
Modulkürzel inf516
Credit points 6.0 KP
Workload 180 h
Institute directory Department of Computing Science
Verwendbarkeit des Moduls
  • Master's Programme Computing Science (Master) >
  • Master's programme Digitalised Energy Systems (Master) >
Zuständige Personen
  • Nieße, Astrid (module responsibility)
  • Lehrenden, Die im Modul (Prüfungsberechtigt)
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:

  1. Multi-agent systems
    • Foundations and definitions
    • MAS architectures
    • Agent communication
    • cooperative and competetive agents MAS
    • learning in MAS
  2. Distributed Optimization
    • CASIMIR
    • Overview on distributed optimization
    • CSP and COP
    • Distributed SCP und COP
  3. Self-organizing energy systems
  4. Applications
    • Virtual Power Plants
    • QEMS and Microgrids
    • DSM and DR
    • Energy market applications
    • Swarms for storage management
    • Multi-purpose examples
  5. Programming part
    • Agent framework mango
    • Co-simulation framework mosaik
    • Power grid simulation pandapower
Literaturempfehlungen
  • 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 1VL + 1Ü
Previous knowledge Fundamentals of Optimization, Fundamentals of Digitized Energy Systems
Form of instruction Comment SWS Frequency Workload of compulsory attendance
Lecture 2 WiSe 28
Exercises 2 WiSe 28
Präsenzzeit Modul insgesamt 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