Work

From comparison to integration: Building energy simulation tool variability and the case for intelligent retrofit workflows

Year: 2025

Type: article

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. • Evaluated 5 EEM packages for Building 101's energy retrofit. • Compared real-world data with simulation outputs from multiple BES tools. • Showcased Asset Score's viability against more complex BES tools. • Highlighted economic impacts of energy retrofitting on projected savings. • Identified need for AI-driven tools in future BES research.

Source: Energy Reports

DOI: 10.1016/j.egyr.2025.12.017

Authors: Amir Safari, Dalya Ismael, Mahsa Safari, James Freihaut

Institutions: Old Dominion University, Pennsylvania State University

Language: English

Topic: Building Energy and Comfort Optimization

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDGs: Climate action, Affordable and clean energy, Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,040