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Priority Ranking of Energy Efficiency Renovation Measures for Existing Buildings Under Budget Constraints: A Hierarchical Decision-Making Framework Integrated with Carbon Revenue Analysis

予算制約下における既存建築物の省エネ改修対策の優先順位付け：炭素収益分析を統合した階層的意思決定フレームワーク (AI 翻訳)

Peng-Chong Cao, J Y Chen, Yang Wen

Buildings📚 査読済 / ジャーナル2026-07-09#省エネOrigin: CN経営インパクト: コスト削減対象セクター: construction
DOI: 10.3390/buildings16142730
原典: https://doi.org/10.3390/buildings16142730

🤖 gxceed AI 要約

日本語

本研究は、炭素取引メカニズムを導入し、ライフサイクル費用便益分析と正味現在価値率（NPVR）に基づく優先順位決定フレームワークを開発。中国西安の老朽化住宅を対象に、外壁断熱、屋根断熱、窓交換、照明更新、屋上太陽光発電の5つの改修対策を評価。照明システム更新と屋上PVが最も高い経済的リターンを示す一方、外皮断熱は初期投資が高くNPVRが低い。電力価格が経済性に最も影響し、炭素価格の影響は限定的。

English

This study develops a priority decision framework for building energy retrofits using life-cycle cost-benefit analysis and net present value rate (NPVR), integrating carbon trading. Five retrofit measures (wall/roof insulation, window replacement, lighting upgrade, rooftop PV) are evaluated on a residential building in Xi'an, China via TRNSYS simulation. Results show lighting upgrades and rooftop PV yield highest economic returns, while envelope insulation has lower NPVR due to high upfront cost. Sensitivity analysis indicates electricity price is the dominant factor, with carbon price having limited influence under current market conditions. The framework provides a quantitative tool for optimizing retrofit investments under budget constraints.

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

日本では多くの既存建築物が更新時期を迎え、省エネ改修はGX実現の鍵である。本フレームワークは、日本の建物に適用可能であり、限られた予算下で炭素収益も考慮した投資判断を支援する。特に、東京都のキャップ＆トレード制度など炭素価格導入事例との比較に示唆を与える。

In the global GX context

Globally, building retrofits are crucial for decarbonization, yet budget constraints hinder investment. This paper introduces a practical decision framework that incorporates carbon revenues into cost-benefit analysis, addressing the common challenge of long payback periods. The finding that electricity price dominates over carbon price is particularly relevant for policymakers designing incentive schemes.

👥 読者別の含意

🔬研究者:Offers a quantitative method combining NPVR and carbon revenue for retrofit prioritization under budget constraints, applicable to various building types.

🏢実務担当者:Building owners and facility managers can use this framework to select cost-effective measures by considering both energy savings and potential carbon revenue streams.

🏛政策担当者:Sensitivity analysis shows electricity price is more influential than carbon price, suggesting policymakers focus on energy pricing to stimulate retrofits.

📄 Abstract（原文）

Reducing carbon emissions while carrying out urban renewal has put existing residential buildings in the spotlight for low-carbon transformation. These buildings typically consume large amounts of energy and offer significant savings potential, making them a priority in the building sector. Addressing the challenges of limited capital, long payback periods, and inadequate comprehensive benefit assessment in building energy retrofits, this study introduces a carbon trading mechanism and develops a priority decision-making framework based on life-cycle cost–benefit analysis and net present value rate (NPVR). Five typical retrofit measures (grouped into four simulation categories), including external wall insulation, roof insulation, window replacement, lighting upgrade, and rooftop photovoltaic (PV) system, are evaluated through TRNSYS energy simulation applied to an aging residential building in Xi’an, China. The results demonstrate that lighting system upgrades and rooftop PV installation yield the highest economic returns and investment efficiency, while building envelope insulation measures, despite delivering substantial energy savings, exhibit lower NPVR due to high initial investment. Sensitivity analysis reveals that electricity price is the dominant factor influencing economic viability, whereas carbon price under current market conditions exerts limited influence on retrofit prioritization. The proposed framework provides a quantitative decision-support tool for building owners and policymakers to optimize retrofit investment strategies under budget constraints.

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