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不確実性下での配電変電所容量への適応的投資のトリガールール最適化：柔軟性の価値の活用

Trigger rules optimization for adaptable investment in distribution substation capacity under uncertainty: Untapping the value of flexibility (原題)

Ruiz Hernandez, Miguel Angel, Gomez San Roman, Tomas, Chaves-Ávila, José Pablo

Zenodoプレプリント2026-08-13#エネルギー転換Origin: EU経営インパクト: コスト削減対象セクター: power
DOI: 10.1016/j.ijepes.2026.112110
原典: https://zenodo.org/records/22058463
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🤖 gxceed AI 要約

日本語

本論文は、不確実性下での配電変電所容量投資のタイミングを最適化する確率的最適化モデルを提案する。リアルオプションとトリガールールを組み合わせ、柔軟性ソリューションとの相乗効果を実証し、従来手法と比較して期待コストを15.1%削減、予約柔軟性を64.9%削減することを示した。適応的戦略は、状況に応じて投資を前倒しまたは延期し、接続迅速化とコスト効率のバランスを取る。規制面では、条件付き承認の可能性を示唆する。

English

This paper proposes a stochastic optimization model for timing distribution substation capacity investments under uncertainty, integrating real options and trigger rules. It demonstrates strong synergies with flexibility solutions, achieving 15.1% expected savings and 64.9% reduction in reserved flexibility compared to traditional approaches. Adaptable strategies balance faster connections and cost-efficiency, and regulatory implications for conditional approval are discussed.

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

日本の配電網では再エネ導入拡大と電化需要増加に伴い、系統混雑や接続待ちが課題となっている。本モデルは、不確実性下での投資判断を支援し、SSBJや有報での設備投資計画の説明にも活用可能。また、系統投資の条件付き承認という規制面での示唆は、日本の系統運用にも参考になる。

In the global GX context

Globally, grid congestion and connection delays are growing concerns as renewable penetration rises. This paper offers a quantitative framework for adaptive grid investment, relevant to regulatory discussions on anticipatory investments and flexibility markets. It contributes to the literature on real options in energy infrastructure and provides evidence for cost savings and flexibility reduction.

👥 読者別の含意

🔬研究者:Provides a novel stochastic optimization model combining real options and trigger rules for grid investment, with significant savings and flexibility reduction.

🏢実務担当者:Offers a decision-support tool for distribution system operators to optimize investment timing and flexibility procurement under uncertainty.

🏛政策担当者:Suggests regulatory mechanisms for conditional approval of anticipatory grid investments to avoid stranded assets.

📄 Abstract（原文）

The rise of intermittent renewable generation and the electrification of demand are causing grid congestion and connection delays in some countries, a trend expected to expand as the energy transition progresses. At the same time, distribution system operators face high uncertainty in forecasting peak loads due to the unpredictable adoption pace of technologies such as electric vehicles, distributed generation, and industrial electrification. This paper presents a stochastic optimization model to determine the optimal timing of substation capacity in- vestments combined with flexibility solutions under uncertainty. The model builds on the real options framework and employs triggers as decision rules (e.g., investing in a transformer once peak load exceeds a threshold), resulting in adaptable strategies, in which future investment decisions are contingent on unfolding information rather than fixed planning schedules. The model optimizes these triggers and reveals strong synergies with flexibility solutions, achieving 15.1% expected savings and 64.9% expected reduction in reserved flexibility compared to the traditional approach in our case study. Adaptable strategies may lead to anticipatory investment in some scenarios and deferral in others compared to the traditional planning approach, striking a balance be- tween faster connections and cost-efficiency. This adaptability is particularly valuable given the current high- uncertainty context. The case study shows that these benefits grow as available flexibility increases. From a regulatory standpoint, these trigger rules can support conditional approval of anticipatory grid investments, contingent on confirmation of the investment need (e.g., peak load exceeding a set threshold), thereby limiting the risk of such investments becoming stranded assets

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