inf516 - Distributed Operation in Digitalised Energy Systems - Campusmanagementsystem Stud.IP

inf516 - Distributed Operation in Digitalised Energy Systems

Department of Computing Science

6 KP

Module components

Semester courses Winter semester 2024/2025

Examination

Lecture

2.01.516 - Agent-based Control in Energy Systems
- Prof. Dr. Astrid Nieße
- Rico Schrage, M. Sc.
Wednesday: 08:00 - 10:00, weekly (from 16/10/24), Location: A03 4-403
Thursday: 16:00 - 18:00, weekly (from 17/10/24), Location: A07 0-031
Dates on Thursday, 06.03.2025 10:00 - 12:00, Wednesday, 12.03.2025 08:00 - 12:30, Location: (Industriestraße 11, Astrid Nieße (0-004))
This course first introduces the basics of software agents and agent systems. Using application examples from the field of energy systems, different aspects are examined, e.g., (distributed) optimization of real-world problems, agent architectures, agent communication, cooperative and competitive agents, and agents to implement distributed heuristics, ... The accompanying exercise is divided into two phases. 1. Phase: Exercise sheets are handed out to put the basics of the lecture into practice 2. Phase: You will get assigned to projects in which a distributed system/algorithm needs to be implemented that can solve a given real-world (from the energy domain) optimization problem. The programming language for the exercises is Python. The framework mango supports the implementation of the distributed system.

Exercises

2.01.516 - Agent-based Control in Energy Systems
- Prof. Dr. Astrid Nieße
- Rico Schrage, M. Sc.
Wednesday: 08:00 - 10:00, weekly (from 16/10/24), Location: A03 4-403
Thursday: 16:00 - 18:00, weekly (from 17/10/24), Location: A07 0-031
Dates on Thursday, 06.03.2025 10:00 - 12:00, Wednesday, 12.03.2025 08:00 - 12:30, Location: (Industriestraße 11, Astrid Nieße (0-004))
This course first introduces the basics of software agents and agent systems. Using application examples from the field of energy systems, different aspects are examined, e.g., (distributed) optimization of real-world problems, agent architectures, agent communication, cooperative and competitive agents, and agents to implement distributed heuristics, ... The accompanying exercise is divided into two phases. 1. Phase: Exercise sheets are handed out to put the basics of the lecture into practice 2. Phase: You will get assigned to projects in which a distributed system/algorithm needs to be implemented that can solve a given real-world (from the energy domain) optimization problem. The programming language for the exercises is Python. The framework mango supports the implementation of the distributed system.

Notes on the module

Prerequisites	Fundamentals of Optimization, Fundamentals of Digitized Energy Systems
Kapazität/Teilnehmerzahl	50
Prüfungszeiten	In the current semester and at the end of the event
Module examination	Portfolio or oral exam or written exam
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