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Ιδρυματικό Αποθετήριο [SANDBOX]
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI: | http://purl.tuc.gr/dl/dias/640D8B73-3EBD-4B5B-9084-F976B38CACC0 | ||
| Έτος | 2019 | ||
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | ||
| Άδεια Χρήσης |
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| Βιβλιογραφική Αναφορά | M.A. Garciá-Fuentes, G. Hernández, V. Serna, S. Martín, S. Álvarez, G.N. Lilis, G. Giannakis, K. Katsigarakis, L. Mabe, X. Oregi, D. Manjarres, H.E. Ridouane and L. De Tommasi, "OptEEmAL: decision-support tool for the design of energy retrofitting projects at district level," in Central Europe towards Sustainable Building, 2019. doi: 10.1088/1755-1315/290/1/012129 https://doi.org/10.1088/1755-1315/290/1/012129 | ||
| Εμφανίζεται στις Συλλογές |
Designing energy retrofitting actions poses an elevated number of problems, as the definition of the baseline, selection of indicators to measure performance, modelling, setting objectives, etc. This is time-consuming and it can result in a number of inaccuracies, leading to inadequate decisions. While these problems are present at building level, they are multiplied at district level, where there are complex interactions to analyse, simulate and improve. OptEEmAL proposes a solution as a decision-support tool for the design of energy retrofitting projects at district level. Based on specific input data (IFC(s), CityGML, etc.), the platform will automatically simulate the baseline scenario and launch an optimisation process where a series of Energy Conservation Measures (ECMs) will be applied to this scenario. Its performance will be evaluated through a holistic set of indicators to obtain the best combination of ECMs that complies with user's objectives. A great reduction in time and higher accuracy in the models are experienced, since they are automatically created and checked. A subjective problem is transformed into a mathematical problem; it simplifies it and ensures a more robust decision-making. This paper will present a case where the platform has been tested.
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