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In this study, the impact of data time resolution on long-term voltage stability assessment of a power grid with high penetration of wind-solar hybrid power plants is investigated. Historical and synthetic wind data as well as solar irradiance are used to calculate power output from hypothetical offshore wind-solar hybrid power plants, geographically located off the coast of Massachusetts, USA. The results show that using hourly input data can overestimate the long-term voltage stability, compared with using minute data. However, the relative difference in terms of voltage mean value and standard deviation is marginal whilst the most significant difference is the intensity of the voltage fluctuations. The main drawback of using high-resolution data is the execution time, increasing proportionally with the number of time steps. Thus, it is argued that the choice of da ta time resolution should be based on the aspects of long-term voltage stability and the size of the power grid to be studied.

In the next decades, the dependencies on power production from renewable energy sources are expected to increase dramatically. A transition towards large-scale offshore wind farms together with an increased electrification of the industry and transportation sectors introduces new vulnerabilities to society. Further, extreme weather events are expected to increase in intensity and frequency, driven by climate change. However, there are significant knowledge gaps concerning the impacts of severe weather conditions on the resilience of power systems with large dependencies on offshore wind. In the present study, a comparison between two different power systems’ resilience to historical extreme storm conditions has been conducted. The power systems are the IEEE39-bus New England model and the Great Britain model. The results show significant differences between the two power systems, which underlying reasons are analysed and explained. With an offshore wind penetration level of 30 %, the New England model stays intact in terms of connected load. When increasing the penetration level to 40 %, about 10 % of the total connected load gets disconnected, whereas about 33 % of the load gets disconnected with a penetration level of 50 %. The Great Britain model stays intact in terms of connected load with a penetration level of at least 49 %.

The electrification of societies and the decarbonisation of electricity production are changing energy systems worldwide. A fast transition towards the replacement of fossil fuels by intermittent renewable energy sources is expected in the next decades to combat climate change. A significant share of the produced electricity is likely to be generated from offshore wind farms, due to the abundant wind resources in the offshore regions and the lack of available onshore sites. However, increased electricity dependence in combination with expanded offshore wind power generation introduce new vulnerabilities to the society. Specifically, the effects of high impact low probability (HILP) events are considered as potential threats to the power system, not least because of the increasing number of extreme weather events. Therefore, research on power grid vulnerability and power system resilience to HILP events are of significant interest.

This thesis presents results of studies investigating power grid vulnerability from a topological perspective, and resilience to storm conditions of power systems with varying dependencies on offshore wind. To achieve this, methods based on complex network theory and AC power flow analysis have been developed, tested, and evaluated. Further, geospatial wind data from historical extreme storm events have been used to generate realistic power production profiles from hypothetical offshore wind farms.

The results strengthen that complex network concepts can be used successfully in the context of power grid vulnerability analysis. Further, the results show that the resilience of power systems with large dependencies on offshore wind differ vastly depending on the grid properties and control strategies, which are further discussed in this thesis.

To reduce the vulnerability of power grids to high impact low probability (HILP) events, analysis methods can be applied to quantify the criticality of the nodes in the grid. The method implemented in this article is one originating from complex network theory. It is used to quantify the structural vulnerability of an open-source transmission grid model representing the Nordic transmission grid. The analytical measures used are clustering coefficient and betweenness, closeness, degree, and combined centrality, which are weighted with respect to the estimated values of the transmission lines’ series reactance. The results, which are presented in the form of geographic and network representations, show substantial differences in terms of criticality between the nodes. The most critical ones are highlighted in geographic representations and are further compared with an open-source system analysis performed by the Swedish transmission system operator (TSO). The outcome from this study is that the weighted and combined centrality measure performed the best in terms of identifying critical nodes in the Nordic transmission grid. Thus, the method can be used as a tool for assessing the structural vulnerability of a real transmission grid, even with limited access to electrical grid data. However, the results from this method should not be considered conclusive.

The ongoing transition towards large installations of offshore wind and the electrification of the transport sector and other critical infrastructures introduce new vulnerabilities to the society. Large dependencies of power production from offshore wind are expected in the next decades, but there are large knowledge gaps regarding the power production reliability under severe weather conditions. Simultaneously, weather extremes may increase in frequency and intensity, driven by climate change. In this paper we investigate the resilience of a power system subject to a hurricane event. The power system is based on the IEEE39-bus New England system but with different scenarios for increasing penetration of offshore wind. We find that an offshore wind penetration level of 30% or less results in a power system resilient to hurricane events, with no need for load disconnection. However, when increased to 40% offshore wind penetration, 650 MW corresponding to 10% of the total load demand gets disconnected during the storm peak. With a penetration of 50% offshore wind, the disconnected load ranges from 2.2 GW of load corresponding to 1/3 of the total load demand, to a total power system blackout.