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.

 

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How MOEEBIUS Indoor Air Quality models are designed? What is the most important advantage of MOEEBIUS district heating and DER system models which are necessary to produce building and district level predictions and enable the implementation of energy efficiency-driven or demand response-driven operational strategies? Please read the latest public reports! They include many interesting information not only about our models and technical innovations, but also about buildings in which the most promising MOEEBIUS solutions are tested. 

The first report, entitled "MOEEBIUS Indoor Air Quality Assessment Models", focuses on the provision of enhanced Indoor Air Quality (IAQ) Models that are able to evaluate indoor hygienic and health/well-being conditions through identifying contamination of the air with various compounds such as carbon dioxide, carbon monoxide and volatile organic compounds. This was accomplished through the development of an improved IAQ model which is integrated with the Energy Management System program. Consequently, adequate Key Performane Indicators can be generated to assess the IAQ which is one of the main aspects of the user's comfort conditions. 

The main goal of the second document, entitled "MOEEBIUS Models of DER devices", is to develop enhanced district heating and Distributed Energy Resources system models which are necessary to provide modelling functions required to produce building and district level predictions (thermal/electric demand, fuel consumption, equipment response). These models also enable the implementation of energy efficiency-driven or demand response-driven operational strategies. 

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Sunday, October 22, 2017

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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.