<p>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. Here 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 owing to weather variability and weather-induced risk. Furthermore, we disentangle short- and long-term resilience challenges (from multi-day to annual scale) with distinct metrics and stress tests to incorporate both into future energy modelling assessments. Our methodology and implementation in an open energy system model (PyPSA-Eur) can be re-applied to other systems and help researchers and policymakers in building more resilient and adequate energy systems.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Resilience metrics to guide back-up investments in the power system during extreme weather

  • Aleksander Grochowicz,
  • Hannah C. Bloomfield,
  • Marta Victoria

摘要

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. Here 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 owing to weather variability and weather-induced risk. Furthermore, we disentangle short- and long-term resilience challenges (from multi-day to annual scale) with distinct metrics and stress tests to incorporate both into future energy modelling assessments. Our methodology and implementation in an open energy system model (PyPSA-Eur) can be re-applied to other systems and help researchers and policymakers in building more resilient and adequate energy systems.