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Model Reduction of Power Grids via Clustering

Berendschot, Joris (2019) Model Reduction of Power Grids via Clustering. Integration Project, Industrial Engineering and Management.

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Abstract

In this project, we are concerned with strategies for the clustering of nodes based on the cluster-based model reduction for power grid networks. To minimize the number of failures in these networks, it is important to know the behaviour. To predict the behaviour of these networks, the size and complexity of the network can be reduced with a model reduction technique. Based on the cluster-based model reduction technique we attempt to find a strategy to cluster nodes. At this stage in the research, analysing a power grid is too big and complex and therefore a toy model of ten nodes is analysed. In the attempt to find a strategy, we want to find patterns in the optimal partitions of structured graphs, random graphs and weighted graphs. We considered two different cases: in case 1 the error is measured considering the weighted differences of the states of neighbouring nodes, and for case 2 the error is measured considering the weighted differences of the states of all other nodes. The error calculations are based on the H2-norm.

Item Type: Thesis (Integration Project)
Supervisor:
Supervisor nameSupervisor E mail
De Persis, C.C.De.Persis@rug.nl
Bosch, A.J.A.J.Bosch@rug.nl
Degree programme: Industrial Engineering and Management
Thesis type: Integration Project
Language: English
Date Deposited: 20 Feb 2019
Last Modified: 21 Feb 2019 15:50
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/19183

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