Bi-Level Optimization Dispatching of Hydrogen-Containing Integrated Energy System Considering Electric Vehicles and Demand Response
電気自動車と需要応答を考慮した水素含有統合エネルギーシステムの二段階最適化運用 (AI 翻訳)
Yiming Liu, Lirong Xie, Yifan Bian, Weishan Song, Chao Hu
🤖 gxceed AI 要約
日本語
電気自動車（EV）の普及に伴い、水素含有統合エネルギーシステム（H-IES）の効率的運用が課題となっている。本研究では、段階的炭素排出量取引メカニズム、需要応答、EVの運用特性を同時に組み込んだ二段階最適化スケジューリング戦略を開発した。上位問題はシステム全体の運用コスト最小化、下位問題はEVユーザーの充電コスト削減を目的とし、KKT条件を用いて解かれる。事例研究では、単段階ベンチマークと比較して総運用コスト34.79％削減、EV充電コスト4.50％削減を実証した。
English
This paper develops a bi-level optimal scheduling strategy for hydrogen-containing integrated energy systems (H-IES) that incorporates a ladder-type carbon emission trading mechanism, demand response, and electric vehicle (EV) characteristics. The upper-level minimizes total operating cost, while the lower-level reduces EV charging cost, solved via KKT conditions. Case study results show a 34.79% reduction in total operating cost and 4.50% reduction in EV charging cost compared to a single-level benchmark.
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
日本でも水素・EVの統合エネルギーシステムやカーボンプライシングへの関心が高い。本論文の二段階最適化手法は、需要応答や炭素取引を考慮した運用戦略として参考になる。
In the global GX context
The bi-level optimization with carbon trading and demand response is relevant globally as energy systems integrate hydrogen and EVs. The method demonstrates cost reduction potential, adding to the literature on carbon pricing in sector-coupled systems.
👥 読者別の含意
🔬研究者:This paper provides a bi-level optimization framework integrating carbon pricing and demand response for hydrogen energy systems, offering a methodological contribution.
🏢実務担当者:The scheduling strategy can guide operators of integrated energy systems in reducing costs and emissions through coordinated EV charging and demand response.
🏛政策担当者:The incorporation of a ladder-type carbon trading mechanism illustrates how carbon pricing can be operationalized within energy system optimization.
📄 Abstract（原文）
The rapid proliferation of electric vehicles (EVs) has introduced significant challenges to the efficient operation of hydrogen-containing integrated energy systems (H-IESs). To cope with these challenges, this paper develops a bi-level optimal scheduling strategy for H-IESs that simultaneously incorporates a ladder-type carbon emission trading mechanism, demand response, and the operational characteristics of EVs. A demand response model is formulated by considering the coupling characteristics of electric and thermal loads. Price-based incentive signals are further designed to coordinate the interactions between the H-IES operator and EV users, enabling flexible resources to actively participate in system scheduling. In the proposed bi-level framework, the upper-level problem aims to minimize the total operating cost of the H-IES, while the lower-level problem seeks to reduce the charging cost of EV users. The resulting bi-level optimization problem is reformulated and solved using the Karush–Kuhn–Tucker (KKT) conditions. Case study results demonstrate that, compared with the single-level benchmark, the proposed bi-level strategy reduces the total operating cost by 34.79% and lowers the EV charging cost by 4.50%.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/math14060956first seen 2026-05-15 17:27:30
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