Operational Energy Assessment and Selective Retrofit Strategy for a 24-Hour Cafe Using EDGE-Based Scenario Analysis

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Authors: Onie Dian Sanitha, Yunida Iashania, Novera Kristianti, Elis Sri Rahayu, Nia Apriliyanti, Taufiqurahman Taufiqurahman, Audy Mirelia W.S, Yusuf Aditya Sihombing
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Abstract

This research evaluates the energy performance of a 24-hour cafe in a tropical context using the EDGE decision-support platform. Cafe Oregano in Palangka Raya, Indonesia, was selected as a case study due to its continuous operation, refrigeration systems, and kitchen appliances, which generate persistent internal loads that challenge conventional assumptions about commercial building energy use. The EDGE baseline simulation produced a very high Energy Performance Index (EPI) of 778.53 kWh/m²/year, corresponding to a 32.50% relative performance, indicating a mismatch between standardised IFC assumptions and actual cafe operational behaviour. After parameter refinement and validation using monthly electricity bills, performance improved to 674.55 kWh/m²/year (+13.36%), reducing annual electricity consumption from 420,858 to 275,215 kWh. Sensitivity analysis showed that HVAC efficiency and zoning delivered the greatest performance gains, followed by envelope and lighting improvements, while refrigeration loads remained structurally dominant. To evaluate real-world feasibility, a selective retrofit scenario based on local Indonesian market costs was developed. The resulting package—roof and partial wall insulation, LED retrofitting, high-efficiency 1 HP HVAC replacement, and basic zoning controls—requires an estimated capital investment of IDR 310–320 million and achieves a simple payback of 1.5–2 years. Overall, the findings confirm that while EDGE effectively identifies relative performance trends, achieving meaningful energy efficiency in cafe typologies requires calibrated scenarios, realistic operational assumptions, and economically grounded interventions.

Fields of Study & Subjects

Building Energy and Comfort Optimization Building energy efficiency and sustainability Sustainable Building Design and Assessment

Publication details

Journal / source
Journal of Artificial Intelligence in Architecture
Volume
5
Issue
1
Pages
47–55
Publication date
3 February 2026
Language
EN