Models and algorithms for low-frequency oscillations in power transmission systems
Date
2018
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Abstract
Energy 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.
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Keywords
Modelling oscillations, Optimal subsets within network graphs, Generating test scenarios