Low-Carbon Economic Dispatch of Integrated Energy Systems Considering Carbon–Energy Trading and IGA-Assisted Compromise Weight Selection
炭素・エネルギー取引とIGA支援の重み選択を考慮した統合エネルギーシステムの低炭素経済運用 (AI 翻訳)
guoxiang hu, Linjun Shi, Feng Wu, Chenyu Wu, Keman Lin
🤖 gxceed AI 要約
日本語
本研究は、多時間スケールの低炭素経済運用フレームワークを提案し、炭素・エネルギー取引と季節的な炭素圧力信号を統合。パークレベルのIESを対象に、IGAとCPLEXを用いて経済性と炭素排出のバランスを最適化。従来シナリオと比較し、炭素排出7.85%減、運用コスト18.39%減を達成。
English
This study proposes a multi-timescale low-carbon economic dispatch framework for integrated energy systems, integrating carbon-energy trading and seasonal carbon-pressure signals. Using IGA and CPLEX, it optimizes a park-level IES, achieving 7.85% carbon reduction and 18.39% cost savings compared to conventional scenarios.
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
日本のエネルギーシステムでは、再生可能エネルギー導入拡大に伴い、需給調整と炭素管理の統合が課題。本フレームワークは、季節変動を考慮した炭素価格シグナルを運用に組み込む点で、日本の電力・熱供給事業者や地域エネルギー管理に示唆を与える。
In the global GX context
Globally, this research contributes to the growing literature on integrated energy system optimization, offering a practical method to align carbon management with operational decisions. It demonstrates how seasonal carbon signals can be embedded into dispatch, relevant for regions with high renewable penetration and carbon pricing mechanisms.
👥 読者別の含意
🔬研究者:Provides a novel multi-timescale optimization framework combining carbon trading and demand response, useful for further research in IES dispatch.
🏢実務担当者:Offers a method to reduce both carbon emissions and operational costs in integrated energy systems, applicable for energy managers and utilities.
🏛政策担当者:Highlights the potential of carbon-energy trading to drive operational efficiency, informing policy design for carbon markets.
📄 Abstract（原文）
Coordinating energy transactions with carbon allowance management is difficult in a multi-energy-coupled integrated energy system (IES) because seasonal carbon information and hourly operation are handled on different timescales. This study develops a multi-timescale low-carbon economic dispatch framework that integrates carbon–energy trading, low-carbon demand response, seasonal carbon-pressure signals, and preference-weight selection. The case study is a park-level electricity–heat–gas–cooling IES comprising two renewable generation technologies, five conversion technologies, five storage technologies, four end-use load types, and external electricity and gas interfaces. Four 24 h profiles—one for each season—are combined into a 96 h representative horizon. Historical renewable-output and load data are used to derive seasonal carbon-pressure signals, which are embedded in electricity, heat, and gas prices. Cooling demand is treated separately through a fuzzy thermal-comfort response. An outer IGA searches the economic preference weight, while CPLEX solves the hourly dispatch problem for each candidate. The selected economic and carbon-emission weights are 0.62 and 0.38, respectively. Compared with the conventional scenario, the complete framework reduces carbon emissions from 1052.92 t to 970.24 t and operating cost from CNY 1,103,420.84 to CNY 900,485.52, corresponding to reductions of 7.85% and 18.39%. In practical terms, the framework converts seasonal carbon-management information into hourly decisions without relaxing explicit comfort limits. The reported gains apply to the modeled 96 h representative horizon and should not be interpreted as annual performance.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18168065first seen 2026-08-09 05:09:30
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