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.

 

Two new publications are available in our special section. Please go there and read about Platform for Automated Technical Building Management Services and using thermostats for infoor climate control in office buildings!

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Click below and see what you can find in the articles!

A Platform for Automated Technical Building Management Services Using Ontology:

https://opus4.kobv.de/opus4-ohm/frontdoor/index/index/docId/247

The deployment of technical building management services is a requirement to further reduce energy demand of future and existing buildings. Automating the process of configuring and deploying technical building management services such as fault detection and diagnosis of technical Equipment seems to be a promising path to intensify the adoption of these services. In this work we present a data processing and analytics execution platform which allows the deployment of ontology-based, automated technical building Management services on a large-scale. We present the platform architecture and results from a reference implementation performing rule-based fault detection on offline air handling unit data.

Using Thermostats for Indoor Climate Control in Office Buildings: The Effect on Thermal Comfort:

http://www.mdpi.com/1996-1073/10/9/1368

Thermostats are widely used in temperature regulation of indoor spaces and have a direct impact on energy use and occupant thermal comfort. Existing guidelines make recommendations for properly selecting set points to reduce energy use, but there is little or no information regarding the actual achieved thermal comfort of the occupants. While dry-bulb air temperature measured at the thermostat location is sometimes a good proxy, there is less understanding of whether thermal comfort targets are actually met. In this direction, we have defined an experimental Simulation protocol involving two office buildings; the buildings have contrasting geometrical and construction characteristics, as well as different building services systems for meeting heating and cooling demands. A parametric analysis is performed for combinations of controlled variables and boundary conditions. In all cases, occupant thermal comfort is estimated using the Fanger index, as defined in ISO 7730. The results of the parametric study suggest that simple bounds on the dry-bulb air temperature are not sufficient to ensure comfort, and in many cases, more detailed considerations taking into account building characteristics, as well as the types of building heating and cooling services are required. The implication is that the calculation or estimation of detailed comfort indices, or even the use of personalised comfort models, is key towards a more human-centric approach to building design and operation.

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Thursday, April 19, 2018

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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.

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