Optimum integration strategy for Energy Efficiency Measures, Energy Conversion Technologies, and Renewable Technologies under various resource constraints
様々な資源制約下における省エネルギー対策、エネルギー変換技術、再生可能エネルギー技術の最適統合戦略 (AI 翻訳)
Navdeep Bhadbhade, Jonas Grand, Benjamin Ong
🤖 gxceed AI 要約
日本語
産業プロセス熱システムの脱炭素化を目的とし、熱交換ネットワーク、ヒートポンプ、太陽熱などの技術を組み合わせた最適な統合戦略を提案。ピンチ解析、LCA、多目的最適化を統合し、Scope1～3排出とコストのトレードオフを分析。連続・非連続プロセスのケーススタディにより、直接熱回収の有効性と、深い脱炭素化には高いコストが必要なことを示した。
English
This study develops a framework integrating Pinch Analysis, LCA, and multi-objective optimization to identify cost-effective decarbonization strategies for industrial heat systems. It evaluates configurations of heat recovery, heat pumps, solar thermal, and biomass, accounting for Scope 1-3 emissions. Case studies show direct heat recovery as the foundation, with deeper decarbonization requiring combinations of renewables and electrification, but with diminishing returns.
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
日本の産業部門では、鉄鋼・化学などの熱需要が大きく、本フレームワークはGX（グリーントランスフォーメーション）実現に向けた具体的な技術選択と投資判断に役立つ。特にScope3を含むライフサイクル思考は、サプライチェーン全体での排出削減が求められる日本の状況に適合する。
In the global GX context
This framework directly addresses industrial heat decarbonization, a key challenge for global net-zero targets. By integrating multiple objectives and supply chain emissions (Scope 3), it aligns with ISSB and CSRD requirements for holistic climate reporting. The trade-off analysis is useful for transition finance decisions.
👥 読者別の含意
🔬研究者:Provides a systematic methodology combining Pinch Analysis, LCA, and multi-objective optimization for industrial heat decarbonization.
🏢実務担当者:Offers a decision-support tool for selecting cost-effective combinations of efficiency, electrification, and renewable technologies.
🏛政策担当者:Highlights the diminishing returns of deep decarbonization, informing subsidy and incentive design.
📄 Abstract（原文）
Stationary fuel combustion and industrial electricity use account for approximately a quarter of global CO2 emissions, making the decarbonization of industrial process heat systems essential for achieving net-zero targets. Key strategies include improving energy efficiency through heat exchanger networks (HENs), electrifying process heat with heat pumps (HPs), and integrating renewable technologies such as solar thermal (ST). However, increasing levels of integration introduce economic and environmental trade-offs as capital costs rise and indirect emissions occur along the supply chain. This study develops a systematic framework that combines Pinch Analysis, Life Cycle Assessment, and multi-objective optimization to identify optimal decarbonization strategies for industrial heat systems. The framework evaluates technically feasible configurations of energy efficiency measures, energy conversion technologies, and renewable technologies while accounting for Scope 1, 2, and 3 emissions and the trade-off between total annual cost (TAC) and total annual environmental impact (TAEI). The methodology is demonstrated using case studies representing continuous and non-continuous industrial processes under favorable and adverse resource conditions. Results show that direct heat recovery consistently underpins cost-effective decarbonization, while additional emissions reductions are achieved through combinations of HP integration, renewable heat supply, and biomass substitution. Pareto analysis reveals a clear region of diminishing returns, where deeper decarbonization requires substantially higher costs.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.2139/ssrn.6499368first seen 2026-05-14 21:12:05
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。