TY - CHAP A1 - Giannakis, Georgios A1 - Kontes, Georgios A1 - Korolija, Ivan A1 - Rovas, Dimitrios ED - Barnaby, Charles ED - Wetter, Michael T1 - Simulation-time Reduction Techniques for a Retrofit Planning Tool T2 - Proceedings of Building Simulation 2017: 15th Conference of IBPSA N2 - The design of retrofitted energy efficient buildings is a promising option towards achieving a cost-effective improvement of the overall building sector’s energy performance. With the aim of discovering the best design for a retrofitting project in an automatic manner, a decision making (or optimization) process is usually adopted, utilizing accurate building Simulation models towards evaluating the candidate retrofitting scenarios. A major factor which affects the Overall computational time of such a process is the simulation execution time. Since high complexity and prohibitive simulation execution time are predominantly due to the full-scale, detailed simulation, in this work, the following simulation-time reduction methodologies are evaluated with respect to accuracy and computational effort in a test building: Hierarchical clustering; Koopman modes; and Meta-models. The simplified model that would be the outcome of these approaches, can be utilized by any optimization approach to discover the best retrofitting option. KW - Simulation KW - Retrofit Planning KW - Meta-models KW - Hierarchical Clustering KW - Gaussian Processes Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:92-opus4-2516 UR - http://www.ibpsa.org/?page_id=962 SN - 978-1-7750520-0-5 SN - 2522-2708 N1 - Funding: 1. FP7-ICT-2011-6: Building as a Service (BaaS, #288409) 2. H2020-EeB5-2015: Optimised Energy Efficient Design Platform for Refurbishment at District Level (OptEEmAL, #680676) 3. H2020-EeB-2015: Modelling Optimization of Energy Efficiency in Buildings for Urban Sustainability (MOEEBIUS, #680517) ER -