Preparing for the worst: Long-term and short-term weather extremes in resource adequacy assessment

TL;DR

This paper presents a method using shadow prices to identify and analyze weather-induced stress events in power systems, emphasizing the importance of resilience capacities and metrics for future energy planning.

Contribution

It introduces a novel approach to classify and assess weather extremes' impact on power system resilience, incorporating short- and long-term metrics within the PyPSA-Eur model.

Findings

Weather extremes cause significant system stress and operational challenges.

Resilience backup capacities are crucial but financially uncertain due to weather variability.

Distinct metrics for short- and long-term resilience improve energy system assessments.

Abstract

Security of supply is a common and important concern when integrating renewables in net-zero power systems. Extreme weather affects both demand and supply leading to power system stress; in Europe this stress spreads continentally beyond the meteorological root cause. We use an approach based on shadow prices to identify periods of elevated stress called system-defining events and analyse their impact on the power system. By classifying different types of system-defining events, we identify challenges to power system operation and planning. Crucially, we find the need for sufficient resilience back-up (power) capacities whose financial viability is precarious due to weather variability. Furthermore, we disentangle short- and long-term resilience challenges with distinct metrics and stress tests to incorporate both into future energy modelling assessments. Our methodology and implementation in the open model PyPSA-Eur can be re-applied to other systems and help researchers and policymakers in building more resilient and adequate energy systems.