A stochastic policy assessment of Spain’s 81% renewable electricity target for 2030
スペインの2030年再エネ電力比率81%目標に対する確率論的政策評価 (AI 翻訳)
Pau Orive, Cristobal Blanco
🤖 gxceed AI 要約
日本語
スペインの2030年再エネ電力比率81%目標について、確率論的ディスパッチモデルを用いて10,000回のモンテカルロシミュレーションを実施。ベースラインシナリオでは目標達成確率はわずか9.06%、楽観シナリオでも14.51%で、目標達成には再生可能エネルギー容量の上位分布実現が不可欠であることを示した。また、原子力発電の維持が再エネを排除する「原子力パラドックス」を定式化。
English
This study assesses Spain's 81% renewable electricity target using a probabilistic dispatch model with 10,000 Monte Carlo simulations. The baseline scenario shows only 9.06% compliance probability, rising to 14.51% under optimistic assumptions. The 'Nuclear Paradox' is formalized: retaining nuclear capacity crowds out renewables, reducing compliance to zero.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本でも2030年電源構成目標（再エネ36-38%）の達成可能性が議論されている。本論文が示す確率論的評価手法や「原子力パラドックス」の概念は、日本のエネルギー政策立案においても、不確実性を考慮した目標設定と原子力と再エネの両立可能性を検討する際に示唆に富む。
In the global GX context
This paper addresses a global gap in energy planning by explicitly modeling joint uncertainties in capacity, fuel, and demand. The 'Nuclear Paradox' finding is relevant for any country balancing nuclear phase-downs with renewable expansion, and the probabilistic methodology can be applied to other regions' renewable targets.
👥 読者別の含意
🔬研究者:The probabilistic dispatch model and Monte Carlo framework for target compliance assessment offer a rigorous methodology applicable to other energy systems.
🏢実務担当者:Utilities and grid operators can use similar stochastic simulations to evaluate investment risks under policy uncertainty.
🏛政策担当者:The study highlights the need for probabilistic target-setting and reveals the trade-off between nuclear baseload and renewable integration.
📄 Abstract（原文）
Spain’s updated National Integrated Energy and Climate Plan (PNIEC) sets an ambitious target of sourcing 81% of national electricity generation from renewable sources by 2030. While official institutional roadmaps validate this target’s feasibility under central capacity plans and test grid adequacy under historical weather variations, they do not account for the joint probability of target compliance under broader capacity, fuel, and demand uncertainties. To bridge this gap, this study develops an independent and transparent probabilistic dispatch model for the Iberian electricity market using Julia (JuMP), calibrated on hourly market data (2020–2024). We embed a 10,000-iteration Monte Carlo framework to evaluate Spain’s 2030 pathway across five strategic configurations: Baseline, Nuclear, Optimistic, Climate Change, and No Batteries. Our simulations reveal a substantial target achievement gap: the Baseline scenario yields an expected renewable share of 73.75%, achieving the 81% target in only 9.06% of simulated futures. Even under an Optimistic configuration, combining accelerated storage deployment with enhanced demand flexibility, the compliance probability reaches just 14.51%. Furthermore, we formalize a Nuclear Paradox : retaining Spain’s 7.1 GW nuclear fleet yields the lowest wholesale prices (61.51 €/MWh) and carbon emissions (3.81 MtCO 2 ), yet its operational inflexibility crowds out variable renewables, reducing target compliance probability to exactly zero. Finally, while Loss of Load Expectation remains at zero across all scenarios due to the retention of backup gas capacity, our findings indicate that achieving the 81% target is heavily dependent on realizing the upper tail of the renewable capacity deployment distributions rather than variations in market prices.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.esd.2026.102068first seen 2026-07-23 05:05:54
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