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dc.contributor.advisorWeihs, Claus-
dc.contributor.authorSurmann, Dirk-
dc.date.accessioned2019-01-02T08:23:07Z-
dc.date.available2019-01-02T08:23:07Z-
dc.date.issued2018-
dc.identifier.urihttp://hdl.handle.net/2003/37856-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-19843-
dc.description.abstractEnergy supply in the European power transmission system undergoes a structural change due to expansion and integration of renewable energy sources on a large scale. Generating renewable energy is more volatile and less predictable because it usually depends on the weather like wind and sun. Furthermore, the increase in power trading as a result of the full integration of national electricity markets into the European transmission system additionally burdens the power network. Higher volatility and increasing power trading consume additional resources of existing transmission lines while construction projects for network extension take a huge amount of time. As a consequence, the available resources within the European network have to be utilised efficiently and carefully. Reducing the security margins of components in power networks leads to higher vulnerability to additional problems. This thesis focuses on two topics with the aim of supporting power transmission systems stability. Firstly, selecting an optimal subset of nodes within a power network with respect to the particular issue of Low-Frequency Oscillation is addressed. A common application is the optimal placement of measurement devices within a power network. By integrating the modelled oscillations as a preprocessor into the algorithm, the constructed subset includes their characteristics and is optimal to measure this type of oscillation. Secondly, simulation software is widely applied to power networks generating data or investigating the potential effects of changed device parameters. The state of the art way manually defines test scenarios to investigate effects. Each test scenario challenges the corresponding transmission system by, e. g. changing device parameters, increasing its power consumption, or disconnecting a transmission line. Instead of relying on the manual generation of test scenarios to check the network behaviour for modified or new components, it is advantageous to employ an algorithm for building test scenarios. These mechanisms ensure that the range of operating conditions is covered and at the same time propose challenging test scenarios much better than manually generated test scenarios. Black box optimisation techniques support this process by exploring the possible space for test scenarios using a specialised criterion. This cumulative dissertation comprises a summary of six papers which deal with modelling of Low-Frequency Oscillations and with the prediction of corresponding values at unobserved nodes within a power transmission system. I will present two published R packages we implemented to simplify the above process. Applying graph kernels in combination with evolutionary algorithms addresses the node selection task. Issues in multimodal optimisation are addressed using contemporary techniques from model-based optimisation to efficiently identify local minima.en
dc.language.isoende
dc.subjectModelling oscillationsen
dc.subjectOptimal subsets within network graphsen
dc.subjectGenerating test scenariosen
dc.subject.ddc310-
dc.titleModels and algorithms for low-frequency oscillations in power transmission systemsen
dc.typeTextde
dc.contributor.refereeLigges, Uwe-
dc.date.accepted2018-11-30-
dc.type.publicationtypedoctoralThesisde
dc.subject.rswkElektrizitätsversorgungsnetzde
dc.subject.rswkNetzplanungde
dc.subject.rswkSchwingungde
dc.subject.rswkSimulationde
dcterms.accessRightsopen access-
eldorado.secondarypublicationfalsede
Appears in Collections:Lehrstuhl Computergestützte Statistik

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