Deviation-Based Operating Reserve Sizing and Market Co-Optimization for Data-Constrained Island Power Systems
データ制約下の島嶼電力系統における偏差ベースの予備力確保と市場同時最適化 (AI 翻訳)
Domínguez-Garabitos MA, Báez-Santana R, Ocaña-Guevara VS, Rivas-Peña YV, Uceta-Acosta RO, Aybar-Mejía ME
🤖 gxceed AI 要約
日本語
本論文は、データ制約のある島嶼電力系統において、過去の極端な需要や発電の偏差から予備力要件を決定し、エネルギーと予備力を同時最適化する市場ベースの枠組みを提案。カリブ海のSIDSを想定した実験では、予備力需要が最大26.7%に達することを示した。従来の固定ルールや確率的手法の中間的な実用的解決策を提供する。
English
This paper proposes a market-based framework for co-optimizing energy and operating reserves in data-constrained island power systems. Reserve requirements are determined from historically observed extreme deviations, avoiding explicit probabilistic modeling. Evaluated on a Caribbean SIDS case study, reserve needs reached up to 26.7% of demand under high variability. The framework reduces non-served energy and improves allocation efficiency, offering a practical intermediate solution.
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
日本では離島電力系統や地域マイクログリッドでVRE導入が進むが、低慣性系統での信頼性確保が課題。本手法はデータ制約下で適用可能な実用的予備力確保策を提供し、離島GX推進に示唆を与える。
In the global GX context
This paper directly addresses the challenge of maintaining reliability with high VRE in island power systems, which are common globally. The framework provides a middle ground between deterministic and probabilistic methods, useful for data-constrained grids in SIDS and other regions.
👥 読者別の含意
🔬研究者:Power systems researchers studying reserve sizing for high-VRE systems will find this intermediate approach valuable for data-constrained environments.
🏢実務担当者:Utility operators and system planners in island grids can adopt this deviation-based method to set reserve requirements without complex probabilistic models.
🏛政策担当者:Policymakers in SIDS can consider this framework to enhance grid reliability while integrating more renewables.
📄 Abstract（原文）
Data-constrained island power systems with increasing shares of variable renewable energy (VRE) face growing challenges in maintaining reliability while preserving market efficiency. Existing reserve sizing practices typically rely on either fixed deterministic rules or data-intensive probabilistic methods, both presenting practical limitations in Small Island Developing States (SIDS). This paper develops a market-based framework for the co-optimization of energy and operating reserves in low-inertia island power systems, in which reserve requirements are determined from historically observed extreme generation or load deviations that represent operationally validated high-risk system conditions, while reserve allocation and pricing emerge from the co-optimization process. By relying on observed operational variability, the proposed approach avoids explicit probabilistic uncertainty modeling while retaining sensitivity to system stress conditions. The approach is evaluated using a stylized island power system representative of Caribbean SIDS. Results show that reserve requirements are highly sensitive to operating conditions, reaching up to 26.7% of demand under high variability and significantly exceeding conventional fixed reserve criteria. The framework reduces non-served energy, improves reserve allocation efficiency, and generates scarcity-consistent reserve prices under stressed conditions. These findings demonstrate that the proposed methodology provides a practical intermediate solution between deterministic and probabilistic reserve sizing approaches while remaining suitable for data-constrained island power systems.
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.20944/preprints202606.0983.v1first seen 2026-06-20 04:53:09 · last seen 2026-06-26 04:37:58
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。