Abstract
As the urgency to address climate change and modernize energy infrastructure grows, the building sector plays a key role in improving energy efficiency and reducing carbon emissions. This study evaluates five energy retrofit strategies for Building 101 at The Navy Yard in Philadelphia, comparing two real-world proposals from energy service companies with three simulation-based packages derived from Building Energy Simulation (BES) tools. The study examined whether advanced BES tools provide greater accuracy and decision-making value compared to simpler alternatives. Electricity savings ranged from 5 % to 40 %, gas savings from 29.7 % to 61 %, and annual cost reductions between $22,495 and $55,383. The most effective package achieved a 40 % reduction in energy use, with a simple payback of 2.8 years, demonstrating strong economic and environmental viability. By directly comparing retrofit outcomes across five independently developed scenarios, each using distinct software, data inputs, and calibration protocols, this study uniquely captures the fragmented reality of energy modeling practice and provides a scalable framework for cross-tool benchmarking. Advanced BES tools produced more detailed outputs but require significant expertise and data, while simpler platforms like Asset Score produced comparable results with lower input demands, making them suitable for early-stage or resource-constrained assessments. The study’s direct comparison across divergent baselines reveals how tool selection influences both technical outcomes and retrofit feasibility. Future research should prioritize AI-driven calibration, digital twins, and adaptive modeling to enhance accuracy, reduce complexity, and support scalable, stakeholder-responsive retrofit planning.
| Original language | English (US) |
|---|---|
| Article number | 108880 |
| Journal | Energy Reports |
| Volume | 15 |
| DOIs | |
| State | Published - Jun 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 13 Climate Action
All Science Journal Classification (ASJC) codes
- General Energy
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