Urban sustainability

Innovative simulation tools

Real-life models

Modelling Optimization of Energy Efficiency in Buildings for Urban Sustainability

MOEEBIUS introduces a Holistic Energy Performance Optimization Framework that enhances current modelling approaches and delivers innovative simulation tools which deeply grasp and describe real-life building operation complexities in accurate simulation predictions that significantly reduce the “performance gap” and enhance multi-fold, continuous optimization of building energy performance as a means to further mitigate and reduce the identified “performance gap” in real-time or through retrofitting.

 

The whole Consortium of MOEEBIUS gathered in beautiful, picturesque venue of Vila Gale Hotel in Ericeira, Portugal, to participate in the 7th General Assembly of the project (20-22/11/2018). This was the time of conclusions since the project will be finalised in April 2019, and the MOEEBIUS experts were mainly focused on results and progress of specific work packages and on remaining work programme.

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The assembly took place between 20 - 22 of November. The first day was dedicated to discussions related to work carried out and results achieved in the frame of technical work packages: WP6 (MOEEBIUS Decision Support System for Holistic Energy Performance Optimization) and WP7 (Pilot Setup and Validation) and the second day the discussion was continued in the area of technical topics (Use-case applications on the pilot sites) but also project's Exploitation Plan with Market Intelligence Activities was analysed together with MOEEBIUS current dissemination activities, including the schedule of project's final conference which is planned for the end of February 2019 in the framework of World Sustainable Energy Days 2019.

During the General Assembly meeting participants had also visited Mafra City hall and Venda do Pinheiro school and kindergarten: pilot site's buildings of MOEEBIUS project.

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Thursday, April 25, 2019

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EU  This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 680517.