Multi-Objective Optimal Scheduling of Integrated Energy Systems Considering Tiered Carbon Trading and Load-Side Demand Response
段階的炭素排出権取引と負荷側デマンドレスポンスを考慮した統合エネルギーシステムの多目的最適スケジューリング (AI 翻訳)
Shuhao Li, Yixin Lin, Xiutao Gao, Baoqing Lin, Yuanyuan Xu
🤖 gxceed AI 要約
日本語
本論文は、段階的炭素排出権取引と負荷側デマンドレスポンスを統合した統合エネルギーシステムの多目的最適スケジューリングモデルを提案する。報奨・罰則型の段階的炭素コストモデルを組み込み、炭素制約を内部化する。拡張イプシロン制約法を用いて運転コストと炭素排出量の最小化を図り、シミュレーションにより運転コスト13.6％、炭素排出量7.0％の削減を実証した。
English
This paper proposes a multi-objective optimal scheduling model for integrated energy systems that integrates tiered carbon trading and load-side demand response. A reward-penalty carbon cost model internalizes carbon constraints. Using the augmented epsilon-constraint method, the model minimizes operating costs and carbon emissions. Simulation results show cost reduction of 13.6% and carbon emission reduction of 7.0% compared to the baseline.
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、カーボンプライシングの導入が進む中、本モデルは系統運用における排出削減とコスト最適化の同時達成手法を示しており、今後の国内エネルギーシステムの低炭素化に示唆を与える。
In the global GX context
This paper contributes to the global literature on carbon trading integration in energy system optimization, demonstrating a practical framework that combines tiered carbon pricing with demand response to enhance both economic and environmental performance.
👥 読者別の含意
🔬研究者:This paper provides a multi-objective optimization framework integrating tiered carbon trading and demand response for integrated energy systems, offering a methodological approach that can be extended to other energy system studies.
🏢実務担当者:The model can be adapted for carbon-constrained scheduling in real energy systems to reduce operating costs and emissions while improving renewable energy utilization.
📄 Abstract（原文）
This paper proposes a multi-objective optimal scheduling model for integrated energy systems (IESs) that incorporates a tiered carbon emissions trading mechanism and load-side demand response (LDR) to promote sustainability. First, a reward–penalty-based tiered carbon cost model is embedded within the IES scheduling framework, internalizing carbon constraints and providing differentiated carbon price signals for emission reduction. Second, a refined demand response model is introduced, categorizing electrical and thermal loads to enhance flexibility in system operation. The demand response strategy allows for temporal load shifting and load reduction, optimizing the overall energy management. Third, the augmented epsilon-constraint method (AUGMECON) is employed to minimize both total operating costs and carbon emissions. Scenario-based simulations are conducted to evaluate system performance under different configurations: the integrated carbon trading and LDR model, a carbon-trading-only approach, and a baseline scenario. The results show that the proposed model achieves the best performance, reducing operating costs by 13.6% and carbon emissions by 7.0% compared to the baseline. Additionally, the combined approach improves renewable energy utilization and reduces reliance on high-carbon energy sources, demonstrating the effectiveness of integrating carbon trading and demand response strategies for low-carbon and sustainable energy system management.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/su18063073first seen 2026-05-05 22:52:21
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