Multi-Objective Optimal Dispatch of Integrated Energy Systems Under Tiered Carbon Pricing: From Economic Arbitrage to Carbon Buffering
段階的炭素価格制度下での統合エネルギーシステムの多目的最適運用：経済的裁定から炭素緩衝へ (AI 翻訳)
Qi Han, Jingyuan Bian, Xiaojing Bai, Jingxin Wei, Shuang Tian
🤖 gxceed AI 要約
日本語
本論文は、段階的炭素価格メカニズムを組み込んだ統合エネルギーシステム（IES）の多目的最適運用フレームワークを提案。太陽光・風力・ガスタービン・蓄電池・P2G等を含むシステムで、IMOPSOアルゴリズムを用いて運用コストと炭素排出の同時最小化を達成。シミュレーションにより、段階的価格が高排出を非線形に罰し、蓄電池を経済的裁定者から炭素緩衝器へと変貌させることを示した。
English
This paper proposes a multi-objective optimal dispatch framework for integrated energy systems (IES) with a tiered carbon trading mechanism. Using an improved MOPSO algorithm, it minimizes operating cost and carbon emissions simultaneously. Simulations show tiered pricing reshapes the Pareto front toward low-carbon outcomes and transforms energy storage from an arbitrageur into a carbon buffer. The optimized configuration reduces costs by 13.1% and emissions by 9.9% while increasing renewable utilization by 8.5%.
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2023年度から一部の企業に対しカーボンプライシングが導入されつつあるが、本論文のような段階的価格設定は、排出量に応じたインセンティブ設計の参考になる。特に蓄電池の運用戦略とP2Gの役割変化は、日本のエネルギーシステムにおける非線形価格メカニズムの有効性を示唆する。
In the global GX context
This study provides a concrete simulation of how tiered carbon pricing drives operational shifts in integrated energy systems, offering evidence for the design of nonlinear carbon pricing mechanisms globally. The insight that storage evolves into a 'carbon buffer' has implications for the role of batteries in decarbonizing grids, relevant to jurisdictions like the EU and US exploring carbon pricing.
👥 読者別の含意
🔬研究者:The IMOPSO algorithm and the concept of energy storage as a carbon buffer provide a novel framework for multi-objective dispatch under nonlinear carbon pricing, applicable to future system optimization studies.
🏢実務担当者:Energy system operators and corporate sustainability teams can use the demonstrated benefits of tiered pricing (cost and emission reductions) to advocate for or design similar incentive structures in their regions.
🏛政策担当者:The simulation results show that tiered carbon pricing can effectively guide IES toward low-carbon operation, offering a policy instrument that balances economic and environmental objectives.
📄 Abstract（原文）
Traditional fixed or linear carbon prices often fail to reflect the nonlinear incentives of real carbon markets. To address this, we propose a multi-objective optimal dispatch framework for integrated energy systems (IESs) incorporating a tiered carbon trading mechanism. The system—comprising photovoltaics, wind power, a gas turbine, energy storage (ESS), power-to-gas (P2G), and grid interaction—aims to minimize operating and carbon trading costs while maximizing renewable utilization. This is solved using an improved multi-objective particle swarm optimization (IMOPSO) algorithm. Simulations across five configurations reveal that tiered pricing nonlinearly penalizes high emissions, reshaping the Pareto front toward low-carbon outcomes. Consequently, the ESS evolves from a simple economic arbitrageur into a proactive “carbon buffer”, absorbing midday photovoltaic surpluses and substituting gas turbine output during evening peaks. Compared to a grid-only baseline, the optimized multi-energy configuration (gas turbine + ESS + P2G) reduced operating costs by 13.1% and carbon emissions by 9.9%, while increasing renewable utilization by 8.5%. Ultimately, this study demonstrates that a well-designed nonlinear carbon pricing mechanism is decisive for guiding the IES to achieve coordinated economic and low-carbon operation.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.3390/en19092234first seen 2026-05-14 23:07:54
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