セメント生産における熱代替率（TSR）向上のための燃料ミックス評価
Fuel Mix Evaluation to Increase Thermal Substitution Rate (TSR) in Cement Production (原題)
Farhan Azizi, Rika Ampuh Hadiguna, Insannul Kami
🤖 gxceed AI 要約
日本語
インドネシアのセメント工場PT Xを対象に、線形計画法でキルン用燃料ミックスの最適化を試みた研究。432変数のモデルでコスト最小化とTSR目標・塩素硫黄許容限界などの制約を同時に評価。シミュレーションではTSRを2.07%から3.41%へ引き上げ、CO2を約16,000トン削減しつつ燃料調達費を約13.9億ルピア削減できることを示した。
English
A linear-programming model optimizes kiln fuel mix at an Indonesian cement plant (PT X), integrating 432 decision variables to minimize fuel procurement cost under TSR, capacity, and chlorine/sulfur constraints. Simulation raises average TSR from 2.07% to 3.41%, cutting ~16,000 tCO2e and saving IDR 1.39 billion in fuel costs. Sensitivity analysis identifies alternative-fuel feeding capacity as the key bottleneck.
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
セメントは日本の排出量取引制度（GX-ETS）でも重点対象。代替燃料・廃棄物利用の最適化は、日系セメント企業のScope1削減と調達コスト最適化の両立に示唆を与える。
In the global GX context
Cement is a hard-to-abate sector central to global decarbonization and CBAM exposure. This cost-constrained optimization of thermal substitution offers a replicable quantitative template for transition planning in emerging-market heavy industry.
👥 読者別の含意
🔬研究者:制約付き最適化でTSRとコスト・排出を同時評価する実証例として参照可能。
🏢実務担当者:代替燃料導入時のコスト・排出・設備制約のトレードオフを定量化する手法が参考になる。
🏛政策担当者:廃棄物由来燃料の許容基準や炭素価格設計がTSR普及に与える影響を検討する材料になる。
📄 Abstract（原文）
The global cement industry is a major energy-intensive sector contributing to world carbon emissions, requiring comprehensive decarbonization efforts. In the case study of kiln units, I, II, and III at PT X, the energy mix is still dominated by coal, with a very low average Thermal Substitution Rate (TSR) of 2.07% in 2022. The transition towards alternative fuel utilization must be planned so as not to violate operational or financial limits. Therefore, this study aims to evaluate the most optimal fuel mix strategy using a mathematical model based on Linear Programming. This quantitative model, which integrates 432 decision variables, functions as an instrument to minimize the total fuel procurement cost. The optimization model evaluates various constraints simultaneously, including specific kiln energy requirements, TSR targets, AF feeding and storage capacities, supply availability, as well as chemical tolerance limits for chlorine and sulfur. Based on a simulation with a 1.26% TSR target, the model recommends a new energy mix composition that increases the average TSR to 3.41%. This fuel allocation shift directly impacts the reduction of greenhouse gas emissions by 16,037,904 kg CO2e, while simultaneously generating a fuel procurement cost savings of IDR 1,391,762,000 compared to the 2022 conditions. The sensitivity analysis proves that this system is highly dynamic in responding to price changes. The model is sensitive to price increases in coal, rice husk, and sawdust through cross-reallocation mechanisms and biomass substitution, but is highly insensitive to price increases in palm fiber. On the other hand, this study identifies the mechanical capacity limitation of the AF feeding system as the primary bottleneck hindering efficiency. Overall, this model provides a quantitative decision-making foundation for the cement industry to achieve a balance between cost efficiency, operational stability, and decarbonization targets. Contribution to Sustainable Development Goals (SDGs):SDG 7: Affordable and Clean EnergySDG 12: Responsible Consumption and ProductionSDG 13: Climate Action
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.29165/ajarcde.v10i3.1403first seen 2026-11-01 04:43:47 · last seen 2026-11-06 04:36:29
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