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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.

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 %.

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.

To mitigate climate change and meet increasing electricity demand, the global installed capacity of renewable energy sources like wind power is rapidly increasing. Further, external threats against the power system are expected to increase. The threats can arise from extreme weather events driven by climate change, or from antagonistic attacks like sabotage or military conflicts. The power grid is extensive and difficult to oversee due to its complexity and size and is therefore sensitive to such threats. Transmission lines are particularly vulnerable due to their exposure to harsh weather and the difficulty in monitoring them, making them susceptible to sabotage. With more wind power and external threats, it is crucial to study how wind farm integration affects power system resilience to severe line outages. In the present study, this scenario is investigated by simulating 29 different grid topologies 1 000 times each though Monte Carlo simulations. Each topology represents a case where conventional generators are replaced by wind farms. Severe line outages are triggered, and the effect is quantified in terms of disconnected load. The results show that replacing conventional generation by wind power can enhance the power system resilience. The outcome is determined by underlaying factors such as the installed wind power capacity, the electrical distance between wind farms, and the electrical distance between wind farms and loads. The finding that deliberate integration of wind power can enhance the resilience of a power system to severe line outages is important knowledge for transmission system operators and policymakers.

The large-scale deployment of renewable energy at sea offers an opportunity to combine complementary resources within shared offshore infrastructure. While co-location of wind, wave, and solar energy has been proposed as a means to reduce variability and costs, the global conditions under which hybrid offshore power parks are economically preferable remain poorly understood. This study performs a global, temporally high-resolved, techno-economic assessment of offshore wind, wave, and floating solar power, both as stand-alone and co-located systems. Using hourly ERA5 reanalysis data for the period 2020–2024, energy generation from each technology is modelled, and the levelized cost of energy (LCOE) for hybrid parks is minimized subject to shared grid infrastructure and curtailment. The optimization is performed for two cost scenarios representing present-day and near-future capital expenditure levels. Results show that LCOE ranges from 0.04–0.16 €/kWh under present-day conditions and 0.02–0.09 €/kWh under near-future scenarios. Co-location is rarely cost-optimal in regions with excellent single-resource conditions, but can yield lower LCOE than single-technology deployment in locations with moderate and complementary resources. Negative correlations between hourly energy profiles, even when weak (−0.3 to −0.2), are shown to systematically reduce LCOE in mixed systems. While the optimal technology mix is sensitive to assumed cost levels, the underlying drivers (solar capacity factor, resource availability and intersource correlation) for co-location remain robust. These findings provide a global perspective on where and why hybrid offshore energy systems can contribute to a cost-efficient and resilient future energy supply.