OptEEmAL: Decision-Support Tool for the Design of Energy Retrofitting Projects at District Level

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. El Ridouane, L. De Tommasi

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


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.

Original languageEnglish (US)
Article number012129
JournalIOP Conference Series: Earth and Environmental Science
Issue number1
StatePublished - Jun 21 2019
EventCentral Europe towards Sustainable Building 2019, CESB 2019 - Prague, Czech Republic
Duration: Jul 2 2019Jul 4 2019

Bibliographical note

Funding Information:
This research work has been partially funded by the European Commission though the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 680676. All related information to the project is available at https://www.opteemal-project.eu.

Publisher Copyright:
© Published under licence by IOP Publishing Ltd.


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