Design of Carbon Capture Processes Under Part-load Operating Conditions
部分負荷運転条件下での炭素回収プロセスの設計 (AI 翻訳)
David Y. Shu, Boxun Huang, Y. G. Kim, Randall Field, R Gracy Gandhi, Sungho Shin
🤖 gxceed AI 要約
日本語
本論文は、石炭火力発電所の部分負荷運転を考慮した溶剤ベースの炭素回収プロセスの設計最適化を提案。確率的最適化とデータ駆動型モデルを用いて計算負荷を低減し、変動する排ガス条件に対応。設計段階で負荷変動を考慮することで、設備サイズと総コストを6-9%削減し、炭素回収コストを0.7-1.7%低減できることを実証。
English
This paper proposes optimal design of solvent-based carbon capture processes considering part-load operation of coal power plants. Using stochastic optimization and a data-driven approach-to-equilibrium model, it reduces computational complexity and accounts for variable flue gas conditions. Incorporating load variability at the design stage reduces equipment size and total plant cost by 6-9%, yielding a 0.7-1.7% reduction in total cost of carbon capture.
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
日本では石炭火力の利用率低減が進む一方、CCUSは重要な脱炭素オプション。本成果は、負荷変動を考慮した設計最適化によりCCSコスト低減に寄与し、日本の火力発電所への適用が期待される。
In the global GX context
Globally, CCUS is critical for decarbonizing power generation. This study demonstrates that accounting for load variability in capture process design can significantly reduce capital costs, making carbon capture more economically viable for dispatchable fossil plants.
👥 読者別の含意
🔬研究者:Provides a methodology for optimizing carbon capture design under variable load conditions using stochastic optimization and data-driven modeling.
🏢実務担当者:Offers guidance on considering load variability in capture plant design to reduce capital costs, relevant for power plant operators.
🏛政策担当者:Highlights the cost reduction potential of flexible carbon capture design, supporting policy for CCUS deployment on dispatchable power plants.
📄 Abstract（原文）
Solvent-based carbon capture can reduce CO2 emissions resulting from a continued reliance on fossil power plants for firm power. These capture processes remove CO2 from flue gases via a solvent. Careful design via process systems optimization can limit the overall cost of carbon capture, which is both capital- and energy intensive. As dispatchable power plants operate to meet varying load demand, the design process needs to account for varying operating points. However, optimizing the design over multiple operating points yields high computational complexity, which is why designs are often based on a single operating point in practice. Here, we identify optimal carbon capture process designs via stochastic optimization, reducing computational complexity through a data-driven approach-to-equilibrium model of the absorption and desorption processes. We represent variable flue gas conditions based on part-load operation data of a representative coal power plant. Accounting for this variability in the design substantially reduces equipment size and total plant cost by 6-9 % at the expense higher operating costs, yielding a reduction in total cost of carbon capture by 0.7-1.7 %. Given the capital intensity of carbon capture, variability of flue gas conditions therefore should be considered at the design stage, particularly if capture is deployed on plants subject to load following.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.48550/arxiv.2607.13232first seen 2026-07-18 05:41:42
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