Evaluation of ‘Dunkelflaute’ event detection methods considering grid operators’ needs

Abstract Weather conditions associated with low electricity production from renewable energy sources (RESs) can result in so called ‘dunkelflaute’ events. For power system relying significantly on RES, such events can pose a risk for maintaining resource adequacy, i.e. the balance between generation and demand. Coincidence of a coldspell can enhance this risk. In this paper, we perform a literature review of different methods to identify dunkelflaute events from hourly RES production and load data alone. We then validate three of these methods by comparing their results with periods of shortage identified from a detailed power system simulation model used by grid operators. Strengths and weaknesses of these methods are discussed in terms of their data requirements, ease of application, and skill in detecting dunkelflaute events. We find that all three dunkelflaute event detection methods have some ability to identify potential energy shortages, but none are able to detect all events. Most likely other factors such as the presence of energy storage capacity, non-weather-dependent outages, and model-related factors limit the skill of these methods. We find that the methods perform best if the residual load is used as input, rather than hourly RES production or load alone. Overall, we find that the method Otero’22, which defines dunkelflaute events as residual load above a given percentile threshold, yields the best results while being straightforward to implement and requiring only data with daily resolution. The results hold for countries relying on a small or a large share of RES production in their electricity mix.