Multi‐Objective Energy Management for an Integrated Energy System With Small Modular Reactors Considering Uncertainty
小型モジュール原子炉を含む統合エネルギーシステムの不確実性を考慮した多目的エネルギー管理 (AI 翻訳)
P. Phu, Truong Hoang Bao Huy, Tien-Dat Le, Tien Dung Le, Seongkeun Park, Daehee Kim
🤖 gxceed AI 要約
日本語
本論文は、小型モジュール原子炉（SMR）を統合したエネルギーシステム（SMR-IES）の二層スケジューリングフレームワークを提案。二酸化炭素排出量、運用コスト、需要側柔軟性を同時最適化するために、改善ε制約法とTOPSISを組み合わせ、はしご型炭素取引メカニズムと多エネルギーデマンドレスポンスを導入。不確実性は情報ギャップ決定理論で処理し、最適解の許容範囲を名目最適値の35%以内に維持する。
English
This paper proposes a bi-layer scheduling framework for an integrated energy system with small modular reactors (SMR-IES). It optimizes operating cost, carbon emissions, and demand-side flexibility using an improved augmented ε-constraint method and TOPSIS. A ladder-type carbon trading mechanism and multi-energy demand response are incorporated. Uncertainty is managed via information gap decision theory, keeping objective deviations within 35% of nominal optimal values.
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、カーボンニュートラル達成に向けて原子力（SMR含む）と再生可能エネルギーの統合が注目されている。本稿の炭素取引メカニズムと需要応答の枠組みは、日本のエネルギーシステム最適化やSSBJ報告の実務に示唆を与える。
In the global GX context
This framework integrates SMRs with renewables and carbon trading, relevant to global energy transition and ISSB-aligned disclosures. The uncertainty handling and multi-objective optimization approach can inform corporate climate risk management and transition planning.
👥 読者別の含意
🔬研究者:Provides a novel bi-layer optimization method combining carbon trading, demand response, and uncertainty modeling for integrated energy systems with SMRs.
🏢実務担当者:Useful for energy utility planners and corporate sustainability teams designing low-carbon energy portfolios with SMRs and carbon pricing.
🏛政策担当者:Offers insights on policy design for carbon trading mechanisms and demand-side flexibility in nuclear-renewable integrated systems.
📄 Abstract（原文）
An integrated energy system (IES) can alleviate energy crises, promote multi‐energy complementarity, and enhance finer‐grained energy development. Nuclear power is clean and efficient, mainly when using small modular reactors (SMRs), which increase power generation, improve system flexibility, and promote a low‐carbon economy. This paper proposes a bi‐layer scheduling framework for a SMR‐connected integrated energy system (SMR‐IES) to optimize operating cost, carbon emissions, and average demand‐side flexibility during the peak period index. The first layer optimizes the multi‐objective operation of SMR‐IES using a hybrid of the improved augmented ε ‐constraint method and the modified technique for order preference by similarity to the ideal solution approach. This framework incorporates a ladder‐type carbon trading mechanism alongside a multi‐energy demand response program with a comprehensive user satisfaction index to account for carbon emissions throughout the entire process while enhancing demand‐side flexibility for the SMR‐IES. The second layer handles uncertainties using the information gap decision theory approach. The proposed method can determine a scheduling operation with predicted renewable energy sources, load, and energy price errors while keeping optimal objective values within acceptable bounds not higher than 35% of the nominal optimal values ( β = 0.35). Moreover, the proposed method offers a more efficient approach to managing uncertainty than stochastic and robust optimization methods.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1155/er/1046502first seen 2026-05-15 17:26:33
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