Understanding the evolution of electricity networks. Modeling a century of Dutch and Hungarian transmission grid growth

Abstract

Transmission grids can be modeled as networks, with the substations and plants as the nodes, and transmission lines as the edges. The present state of such a network is the result of a complex process of network growth and development, often spanning more than a century in time. Due to a lack of data on the historical state of transmission grids, it has been difficult to study this process. In this thesis, we present a unique new dataset of the historical development of the Dutch transmission grid, reconstructed from hundreds of old maps. Using network analysis, we analyze the network evolution of Dutch grid and compare it an existing dataset of the Hungarian grid. After rapid early network growth, the networks mature in the 1970s, after which many important network characteristics stabilize. We also find that both networks exhibit strong preferential attachment, meaning that nodes with higher degrees are more likely to receive new connections. This leads to an exponential degree distribution. We use a synthetic network generator to try to model the observed growth. Even though the model used is simple, the simulated networks comes close to the real-world evolution on a number of network characteristics. However, since there is no preferential attachment assumed, the degree distribution is concentrated at the lower degrees. We also track the evolution of the network vulnerability, looking both at the topological vulnerability and the change in the optimal power flow after node removal. We find that the topological vulnerability of the real-world networks also stabilizes after the 1970s, although the Dutch networks vulnerability is higher than that of the Hungarian network. The synthetic networks however do not show a drop in vulnerability, and vulnerability stays much higher than those found in the real-world networks. We find little correlation between the topological vulnerability, and the vulnerability calculated using the optimal power flow.