Approximating optimal building retrofit solutions for large-scale retrofit analysis
نویسندگان
چکیده
Coordinated large scale building retrofit is one of the most effective approaches not only to reduce environmental footprint existing buildings but also assure that climate goals can be met. Existing bottom-up become infeasible or lack in terms accuracy and/or computational cost especially when application increases size. Hence, aim this paper propose and develop a approach for large-scale with use scalable building-level surrogate model. To ensure scalability generalization areas, we artificial neural networks. The developed consists set networks trained on archetypes, aiming predict near-optimal solutions all residential Switzerland. This achieved small inputs, within short run time. In order validate approach, compare it conventional mixed simulation optimization approach. model computes solutions, an average coefficient determination 0.91 f1 score 0.89. illustrate advantages model, perform analysis case study Geneva municipality. Such capable providing insights into overall potential areas thus shall support reaching energy emission reduction targets buildings.
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ژورنال
عنوان ژورنال: Applied Energy
سال: 2023
ISSN: ['0306-2619', '1872-9118']
DOI: https://doi.org/10.1016/j.apenergy.2022.120566