Multi-threshold time series analysis enables characterization of variable renewable energy droughts in Europe

TL;DR

This paper introduces a multi-threshold analysis method to better characterize and understand the frequency, duration, and severity of renewable energy droughts in Europe, highlighting the importance of considering multiple thresholds for resilient energy system planning.

Contribution

It develops a multi-threshold framework for analyzing renewable droughts, revealing the limitations of single-threshold approaches and emphasizing the role of drought characteristics in energy storage planning.

Findings

Multi-threshold analysis captures drought variability more effectively.

Extreme drought events can last over 50 days with significant renewable shortfalls.

Single-year analyses are inadequate for modeling weather-resilient energy systems.

Abstract

Variable renewable energy droughts, so called Dunkelflaute events, emerge as a challenge for climate-neutral energy systems based on variable renewables. Here we characterize European drought events for on- and offshore wind power, solar photovoltaics, and renewable technology portfolios, using 38 historic weather years and an advanced identification method. Their characteristics heavily depend on the chosen drought threshold, questioning the usefulness of single-threshold analyses. Applying a multi-threshold framework, we quantify how the complementarity of wind and solar power temporally and spatially alleviates drought frequency, return periods, duration, and severity within (portfolio effect) and across countries (balancing effect). We identify the most extreme droughts, which drive major discharging periods of long-duration storage in a fully renewable European energy system, based on a policy-relevant decarbonization scenario. Such events comprise sequences of shorter droughts of varying severity. The most extreme event occurred in winter 1996/97 and lasted 55 days in an idealized, perfectly interconnected setting. The average renewable availability during this period was still 47% of its long-run mean. System planners must consider such events when planning for storage and other flexibility technologies. Methodologically, we conclude that using arbitrary single calendar years is not suitable for modeling weather-resilient energy scenarios.