In the EU, the building sector significantly impacts energy consumption and greenhouse gas emissions, accounting for 40% of the total energy use and 35%ofemissions, mainly due tothe energy inefficiency of the building stock. Withenergydemandexpectedtoincreaseoverthenextdecade,improvingbuilding energyefficiencyisessential for meetingEUsustainabilitygoals.BuildingEnergy Models (BEMs) are crucial for evaluating and enhancing building performance throughout their lifecycle. However, a notable “energy performance gap” usually exists betweenpredictedandactualenergyuse,exacerbatedbychallengesinaccurately inputting numerous variables and the simplifications inherent in modeling. BEM calibration (BC) approaches are often adopted to reduce these discrepancies, aimed at adjusting model inputs to match output with the observed data. Yet, there is not a universal consensus on which is the best calibration method, with manual and automated approaches offering different benefits. Automated methods, especially those using optimization algorithms, have gained prominence for their efficiency and ability to handle uncertainties. However, BC still significantly depends on the energy modelers’ expertise. This paper introduces a novel software tool for automated BC, aiming to simplify the process by integrating expert knowledge, sensitivity analysis, and optimization algorithms techniques in a unique workflow. This tool reduces the dependence of BC success on modeler expertise, representing a significant step towards more accessible automated BC in the research field and engineering practice, thence allowing a more effective design of energy conservation measures.
A Novel Software Tool for Automated and Integrated Building Energy Model Calibration / Maracchini, Gianluca; D'Orazio, Marco; Di Giuseppe, Elisa; Marco Revel, Gian. - (2024), pp. 471-488. [10.1007/978-3-031-71863-2_30]
A Novel Software Tool for Automated and Integrated Building Energy Model Calibration
Gianluca Maracchini
Primo
;
2024-01-01
Abstract
In the EU, the building sector significantly impacts energy consumption and greenhouse gas emissions, accounting for 40% of the total energy use and 35%ofemissions, mainly due tothe energy inefficiency of the building stock. Withenergydemandexpectedtoincreaseoverthenextdecade,improvingbuilding energyefficiencyisessential for meetingEUsustainabilitygoals.BuildingEnergy Models (BEMs) are crucial for evaluating and enhancing building performance throughout their lifecycle. However, a notable “energy performance gap” usually exists betweenpredictedandactualenergyuse,exacerbatedbychallengesinaccurately inputting numerous variables and the simplifications inherent in modeling. BEM calibration (BC) approaches are often adopted to reduce these discrepancies, aimed at adjusting model inputs to match output with the observed data. Yet, there is not a universal consensus on which is the best calibration method, with manual and automated approaches offering different benefits. Automated methods, especially those using optimization algorithms, have gained prominence for their efficiency and ability to handle uncertainties. However, BC still significantly depends on the energy modelers’ expertise. This paper introduces a novel software tool for automated BC, aiming to simplify the process by integrating expert knowledge, sensitivity analysis, and optimization algorithms techniques in a unique workflow. This tool reduces the dependence of BC success on modeler expertise, representing a significant step towards more accessible automated BC in the research field and engineering practice, thence allowing a more effective design of energy conservation measures.File | Dimensione | Formato | |
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