Modeling Optimization of Energy Efficiency in Buildings for Urban Sustainability
(Duration 11-2015 — 04-2019 Funding: H2020)
MOEEBIUS is an answer to H2020-EeB-2015 call in the topic ‘new tools and methodologies to reduce the gap between predicted and actual energy performances at the level of buildings and blocks of buildings’.
The project consortium involves 15 partners representing research institutions, ESCOs, SMEs, universities and public bodies from 10 countries.
With the increasing demand for more energy efficient buildings, the construction and energy services industries are faced with the challenge to ensure that the energy performance and savings predicted during energy efficiency measures definition is actually achieved during operation. There is, however, significant evidence to suggest that buildings underperform, illustrating a so-called ‘performance gap’, which is attributed to a variety of causal factors related to both predicted and in-use performance, implying that predictions tend to be unrealistically low whilst actual energy performance is usually unnecessarily high.
MOEEBIUS introduces a Holistic Energy Performance Optimization Framework that enhances current (passive and active building elements) 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 optimalization of building energy performance as a means to further mitigate and reduce the identified ‘performance gap’ in real-time or through retrofitting
Almende builds software solutions targeted at providing insights relevant to retrofitting buildings with energy saving solutions. This software will analyse actual performance data of buildings to identify the “performance gap”, and suggest multiple strategies that can be employed for retrofitting.
The project contributes to Almende’s vision on the Energy domain, specifically when it comes to creating awareness about drivers of energy waste within a network (ie. a household or cluster of households), and presenting strategies to reduce or eliminate these drivers.
Smart buildings, energy savings, energy performance, simulation