Linking design and operation performance analysis through model calibration: Parametric assessment on a Passive House building
| Autor: | Patrick James, Massimiliano Manfren, Lamberto Tronchin |
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| Přispěvatelé: | Lamberto Tronchin, Massimiliano Manfren, Patrick AB. James |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Computer science
020209 energy 0211 other engineering and technologies 02 engineering and technology Industrial and Manufacturing Engineering Passive House building performance simulation performance monitoring Robustness (computer science) 021105 building & construction behavioral modelling 0202 electrical engineering electronic engineering information engineering parametric modelling Electrical and Electronic Engineering Baseline (configuration management) Civil and Structural Engineering Parametric statistics Mechanical Engineering Design of experiments Regression analysis Building and Construction Pollution Reliability engineering General Energy Passive house Passive solar building design multivariate regression Architectural technology |
| Popis: | Efficient buildings are an essential component of sustainability and energy transitions, which represent today a techno-economic and socio-economic problem. New paradigms are emerging both for new and existing buildings (e.g. NZEBs) and passive design strategies are becoming increasingly common. However, the adoption of these strategies in mild climates has to be carefully evaluated to prevent overheating in intermediate seasons and increasing cooling loads in summer, considering also climate change scenarios. Additionally, optimistic assumptions about building technology performance are often considered and the variability of occupant comfort preferences and behaviour is generally neglected in the design phase. The research presented aims at verifying the suitability of a simple, robust and scalable calibration approach (based on multivariate linear regression) to link design and operational performance analysis transparently, using a Passive House case study building. First, the original baseline design configuration is compared with a larger spectrum of data generated by means of parametric simulation, following a Design of Experiment (DOE) approach. After that, regression models are trained first on simulation data and then progressively calibrated on measured data during a three year monitoring period. The two fundamental objectives are evaluating the robustness of design phase performance analysis through parametric simulation (i.e. detecting potentially critical assumptions) and maintaining a continuity with operation phase performance analysis (i.e. exploiting the feed-back from measured data). |
| Databáze: | OpenAIRE |
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