Variable renewable energies (VRE), in particular wind and solar PV, constitute a key option to reduce global greenhouse gas emissions. Future policy scenarios therefore propose a dominant role for VRE. However, relying almost entirely on the stochastic weather-determined output of VRE will require a transformation of the way power systems are planned and operated: a growing amount of flexibility will be needed to match variable demand with increasingly variable supply. Due to the complexity of power systems as well as their long investment cycles, it is crucial to prepare the strategic development of flexibility now. The key question for the transition to energy systems based on variable renewables becomes: “How can we ensure that future power systems have the flexibility needed to match demand and variable supply?” Power system operators and regulators need to assess the current flexibility level in their system, analyze all possible flexibility options, and clearly prioritize the needed actions. This paper presents the Flexibility Tracker, an assessment methodology developed to monitor and compare the readiness of power systems for high VRE shares. The Flexibility Tracker builds 14 flexibility assessment domains, by screening systems across the possible flexibility sources (supply, demand, energy storage) and enablers (grid, markets), via 80 standardised Key Performance Indicators (KPIs) scanning the potential, deployment, research activities, policies and barriers regarding flexibility. The methodology allows monitoring the progress made in individual power systems with respect to their potential for integrating VRE, comparing and ranking of different systems, and identifying best practices, common challenges and needed actions to enable and advance flexibility. It ensures that the complex flexibility question has a clear reference which looks at all relevant flexibility options, without being restricted to a single technology scope. As such it provides a useful instrument for market actors operating in multiple countries, as well as policy makers. As case study, the paper presents a comparative assessment of key European systems using this methodology. The results show that the although flexibility deployment depends on the specifics of each system, a coordinated approach would be beneficial as there are clear no-regret options that face barriers in some systems.

In this paper, a risk-based security assessment methodology is presented, which allows the assessment of operational security of a power system’s future state under uncertainty deriving from varying topology scenarios (contingencies) and forecast errors (loads and renewable infeeds). The methodology models input uncertaintywith a copula function-based Monte–Carlo (MC) framework. Furthermore, it provides the highest level of accuracy on initiating causes of failures through an AC power flow (AC PF) framework. Finally, it achieves speed in solution by the combination of twomeasures of risk. A fast screening tool, based on severity functions, allows us to quickly screen the system for the most severe states. A detailed analysis tool, based on an AC optimal power flow (AC OPF) framework and the notion of lost load, provides additional valuable information, including remedial actions to steer away from severe system states. This paper presents results from the application of the methodology proving the necessity of such a framework. It is shown that not taking into account stochastic
dependence through a proper MC setup seriously underestimates system risk and that an AC framework is needed, as voltage deviations are shown to often be initiators of system collapse.