FB18 Elektrotechnik und Informationstechnik

Voraussetzungen
Recommended are „ Terminology, Medical Morphology and Applied Anatomy“ and „ Natural Scientific Principles for Medical Engineering“

Lehrinhalte
Three-phase network and symmetrical components; overhead lines; cables; transformers; calculation of short-circuit currents; switch equipment; switchgears

Literatur
Script, lecture slides, guiding questions, excercises

Voraussetzungen
Contents of the lecture Electrical Power Engineering

Lehrinhalte
The lecture reviews the different levels of energy management. It then focuses on economic dispatch and discusses its different use cases like optimization of self-consumption, virtual power plants, electric vehicle load management or multi-modal neighborhood optimization. Relevant knowledge about the components to be controlled as well as the markets to be addressed is explained.
After this introduction to economic dispatch‘s application environment, the lecture focuses on the methods employed. The underlying mathematical formulations as different types of optimization problems (LP, MILP, QP, stochastic optimization) are reviewed. In parallel, a practical introduction to numerical optimization is given (descent algorithms, convergence, convexity, programming languages for the formulation of optimization problems). Moreover, an introduction into simple methods for the prognosis of future values (linear regression) is provided.All methodological learning is accompanied by hands-on exercises using the Matlab/Octave and the GAMS/AMPL software environments.

Literatur
Boyd, Vandenberghe: Convex Optimization, Cambridge University Press, 2004A GAMS Tutorial by Richard E. Rosenthal, https://www.gams.com/24.8/docs/userguides/userguide/_u_g__tutorial.html

Voraussetzungen
Standard knowledge of linear algebra and multivariate analysis as well as basic knowledge in the use of Matlab/Octave is required. Knowledge of the modules „Kraftwerke & EE“ or „Energiewirtschaft“ is helpful but not necessarry.

Lehrinhalte
The course covers the following topics:
[list]
[*]The basic concepts of stochastic
[*]The sampling theorem
[*]Discrete-time noise processes and their properties
[*]Description of noise processes in the frequency domain
[*]Linear time-invariant systems: FIR and IIR filters
[*]Filtering of noise processes: AR, MA, and ARMA models
[*]The Matched filter
[*]The Wiener filter
[*]Properties of estimators
[*]The method of least squares
[/list]

Literatur
Lecture notes and slides can be downloaded here:
[list]
[*][url]http://www.spg.tu-darmstadt.de[/url]
[*]Moodle platform
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Further reading:
[list]
[*]A. Papoulis: Probability, Random Variables and Stochastic Processes. McGraw-Hill, Inc., third edition, 1991.
[*]P. Z. Peebles, Jr.: Probability, Random Variables and Random Signal Principles. McGraw-Hill, Inc., fourth edition, 2001.
[*]E. Hänsler: Statistische Signale; Grundlagen und Anwendungen. Springer Verlag, 3. Auflage, 2001.
[*]J. F. Böhme: Stochastische Signale. Teubner Studienbücher, 1998.
[*]A. Oppenheim, W. Schafer: Discrete-time Signal Processing. Prentice Hall Upper Saddle River,1999.
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