Comparison of network representations for analysing temporal power plant data

As renewable energy is increasingly used in power generation, the temporal and spatial
balance of electric power supply and demand requires large-scale power transmission to maintain. Describing such systems requires network modeling theory. This dissertation takes the German power transmission network as an example and explores the impact of different representations. The representation forms include unweighted
network, weighted network, multiplex network and interconnected network. In this dissertation, the static topological characteristics of networks under different representations are examined. Then, the temporal data of the available capacity is also introduced, and a temporal network with the power flow path as the time variable is constructed based on Djikstra’s algorithm. In this research, we find that the weighted network is more suitable for modeling transmission networks than the unweighted network, and the multi-layer network may be more suitable for modeling more complex systems.

Description of the figure: Power grid network as a multiplex network. Each layer has the same set of nodes. Green edges represent DC lines. Yellow edges represent 380kV AC lines. Red edges represent 220kV AC lines. Dashed edges are interlayer edges that link the same nodes in different layers.