Examples of models for signal and systems. Introduction to stochastic processes. Modelling of dynamic systems with physical and empirical modelling. Parameter estimation in dynamic models; linear regression, the least squares method and prediction error methods. Black box and grey box modelling. Methods for model validation. Possibilities and limitations with empirical modelling. Overview of some modelling problems in energy systems.
Project: There are several project proposals to choose from, e.g. empirical modelling of some systems with relevance to energy systems.
Lectures, lessons, tutorials and laboratory work.
Passed mini project and passed laboratory course are required. Complementary written examination may occur.
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.