Efficient Networks
| Degree programme | Sustainable Energy Systems |
| Subject area | Engineering & Technology |
| Type of degree | Master Part-time Winter Semester 2023 |
| Course unit title | Efficient Networks |
| Course unit code | 072722010502 |
| Language of instruction | German |
| Type of course unit (compulsory, optional) | Compulsory optional |
| Teaching hours per week | 2 |
| Year of study | 2023 |
| Level of the course / module according to the curriculum | |
| Number of ECTS credits allocated | 3 |
| Name of lecturer(s) | Klaus RHEINBERGER |
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- Implementation with an open source algebraic modeling language and different solvers.
- Fundamentals of graph theory
- modeling of typical building blocks in a networked power system: (MI)LP, binary variables, discretization of ODE
- typical objective functions in a networked power system: costs, peak load
- typical problem classes like transportation problem, assignment problem, transshipment problem, maximum flow problem, minimum-cost flow problem, shortest path problem
- Application examples: battery storage with efficiencies, hot water boiler, PV system, thermally coupled rooms of a building, EVs including minimum charging power, power plants, heat pumps, electrical and thermal grids, transport networks
After completing the course, students will be able to optimize networked techno-economic systems. They can
- give an overview of optimization methods for networked problems and evaluate their suitability for certain problems.
- apply suitable optimization methods to networked problems and interpret their results and sensitivities.
- model typical building blocks in a networked power system and optimize the system with respect to various objective functions.
- understand basic elements of graph theory and identify them in energy-related applications.
- Implement networked systems using an open source modeling language and solve with different solvers.
Integrated Course
- Assessment of exercises (40%)
- Oral or written exam (60%)
For a positive overall grade, at least 50% of the points must be achieved in each part of the examination.
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- Schellong, Wolfgang (2016): Analyse und Optimierung von Energieverbundsystemen. 1. Aufl. 2016. Berlin Heidelberg: Springer Vieweg.
- Hamacher, Horst W. (2006): Lineare Optimierung und Netzwerkoptimierung: Zweisprachige Ausgabe Deutsch Englisch. 2., verb. Aufl. 2006. Wiesbaden: Vieweg+Teubner Verlag.
- Knieps, Gunter (2007): Netzökonomie. 2007. Aufl. Wiesbaden: Gabler Verlag.
- Bertsekas, Dimitri P. (1998): Network Optimization: Continuous And Discrete Models. Belmont, Mass: Athena Scientific.
- Bazaraa, Mokhtar S.; Jarvis, John J.; Sherali, Hanif D. (2010): Linear Programming and Network Flows. 4. Hoboken, N.J: Wiley.
- Easley, David; Kleinberg, Jon (2010): Networks, Crowds, and Markets: Reasoning about a Highly Connected World. New York: Cambridge University Press.
- Turau, Volker; Weyer, Christoph (2015): Algorithmische Graphentheorie. 4th edition. Berlin, Boston: De Gruyter. Online im Internet: DOI: 10.1515/9783110417326 (Zugriff am: 05.08.2019).
Presence Course with obligation to be present