Can Carbon-Aware Electric Load Shifting Reduce Emissions? An Equilibrium-Based Analysis
カーボンアウェアな電力負荷シフトは排出削減に有効か？均衡ベースの分析 (AI 翻訳)
Wenqian Jiang, Olivier Huber, Michael C. Ferris, Line Roald
🤖 gxceed AI 要約
日本語
本論文は、水素製造やデータセンターなどのカーボンセンシティブな電力負荷が、炭素排出削減のために負荷シフトを行う際に、平均排出係数に基づく信号が有効かどうかを分析する。カーボンアウェアな市場均衡モデルを構築し、IEEE RTS-GMLCシステムでのシミュレーションにより、平均炭素排出信号の限界を明らかにした。
English
This paper examines whether carbon-aware load shifting by consumers like hydrogen producers and data centers effectively reduces carbon emissions. It develops an equilibrium model incorporating carbon sensitivity into market clearing and reveals limitations of using average carbon emission signals through simulations on the IEEE RTS-GMLC system.
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
本論文は、カーボンシグナルを電力市場に統合する点で日本のGX政策に関連。特に再生可能エネルギーと水素への依存が高まる中、カーボンアウェア負荷シフトの知見は系統運用と脱炭素戦略に貢献しうる。ただし使用されたテストシステムは米国ベースのため、国内適用にはデータ調整が必要。
In the global GX context
This paper contributes to global discourse on carbon-aware demand response and the effectiveness of carbon intensity signals. It challenges the use of average emission factors in green grids, showing that more nuanced signals are needed for genuine emission reductions, which is relevant for regions with high renewable penetration and flexible loads.
👥 読者別の含意
🔬研究者:Researchers in emission-aware demand response and electricity market design will find the equilibrium model a novel tool for analyzing carbon signal effectiveness.
🏢実務担当者:Corporate sustainability teams managing flexible loads can learn the limitations of average carbon intensity and inform their load shifting strategies.
🏛政策担当者:Policymakers should note that current carbon labeling may misguide load shifting; improved carbon signals are necessary for effective decarbonization.
📄 Abstract（原文）
An increasing number of electric loads, such as hydrogen producers or data centers, can be characterized as carbon-sensitive, meaning that they are willing to adapt the timing and/or location of their electricity usage in order to minimize carbon footprints. However, the emission reduction efforts of these carbon-sensitive loads rely on carbon intensity information such as average carbon emissions, and it is unclear whether load shifting based on these signals effectively reduces carbon emissions. To address this open question, we design a carbon-aware equilibrium model, which expands the commonly used equilibrium model for standard (carbon-agnostic) electricity market clearing to include carbon-sensitive consumers that adapt their consumption based on average carbon emission signals and carbon costs. This analysis represents an idealized situation for carbon-sensitive consumers, where their carbon preferences are reflected directly in the market clearing, and contrasts with current practice, where carbon emission signals only become known to consumers a posteriori (i.e., after the market has already been cleared). Furthermore, we extend our model to consider temporal load shifting and time-varying maximum renewable generations. We employ illustrative three-bus examples and numerical simulations on the IEEE RTS-GMLC system to reveal the limitations of the widely adopted average carbon emission signal for guiding carbon emission reduction. Our model offers a novel perspective for evaluating the effectiveness of different carbon signals and contributes to new carbon signal design.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1145/3744255.3798127first seen 2026-07-06 04:44:34
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