Skip to main content
European Commission logo print header

Modelling Optimization of Energy Efficiency in Buildings for Urban Sustainability

Periodic Reporting for period 3 - MOEEBIUS (Modelling Optimization of Energy Efficiency in Buildings for Urban Sustainability)

Reporting period: 2018-05-01 to 2019-04-30

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. However post-occupancy evaluation studies in built and occupied buildings have demonstrated significant gaps between predicted and actual energy consumption. One of the main reasons of the overall problem – called the performance gap – is the inability of current modelling processes to consider realistic use and operation of buildings. This inevitably leads to significant uncertainties in energy predictions, which in turn prohibits the scaled deployment of energy efficiency projects, effectively hindering the development of the energy services market. Consequently, the successful penetration and effective application of ESCO business models relies on minimizing the gap between actual and predicted building energy performance whilst enabling the introduction of new business models through the utilization of enhanced energy performance prediction and real-time optimization features.

MOEEBIUS directly addresses the aforementioned needs with the introduction of 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. The MOEEBIUS Framework comprises the configuration and integration of an innovative suite of end-user tools and applications enabling improved building energy performance assessment, precise allocation of detailed performance contributions of critical building components, near real-time building performance optimization, optimized retrofitting decision making and near real-time peak-load management optimization at the district level.

MOEEBIUS focuses on the successful realization of a blend of technical, social, environmental and business objectives, which address and reflect the project’s multi-fold approach:
· Advance the capabilities of current building and district energy performance simulation tools, to enable accurate predictions through addressing current modelling and measurement & verification inefficiencies
· Optimize the performance gap through human-centric fine grained control, predictive maintenance and retrofitting at building and district level
· Enable the efficient integration of distributed and intermittent energy resources into the Smart Grid
· Facilitate Energy Performance Contracting penetration in EU Energy Services Markets through the provision of a replicable and easily transferable framework
· Introduce Novel ESCO Business Models and New Energy Market Roles enabling the transition to demand-driven Smart Grid Services through Demand Side Aggregators

The innovative MOEEBIUS solutions are validated in real-life conditions over an extensive pilot roll-out period in a variety of buildings. This evaluation is performed under different environmental, social and cultural contexts/criteria in three dispersed geographical areas: London (UK); Mafra (PT); and Belgrade (RS).
MOEEBIUS framework comprises two main inter functional parts individually composed by the main components developed during the project:
· The MOEEBIUS PIPE is the data acquisition and management layer.
· The MOEEBIUS QUEST is the algorithmic modelling and decision making support layer.

The most important results, components and exploitable outputs of MOEEBIUS are:
· Building Energy Performance Simulation System
· District Energy Prediction System
· Distributed Energy Resources Models Library
· EnviroNOD
· Building and District Level Middleware Configuration and Sensors and Actuators Management
· Dynamic Assessment Engine
· Context Aware Profiling Engine
· Data Analytics Engine
· Predictive Maintenance Advisor Module and VR Environment
· Retrofitting Advisor Tool
· Facility Manager Tool and Decision Support System Graphical User Interface
· End-user interface (mobile app)

MOEEBIUS Consortium released 17 project publications (articles in peer-reviewed scientific journals, publications in conference proceedings, dissemination magazines, etc.), including 15 open access publications, participated in 60 different thematic events: 39 conferences, 1 organized conference, 1 fair trade, 1 brokerage event, 15 workshops and 3 other events.

Targeted living lab dissemination and training workshops were performed (3 in each pilot site) to a) raise awareness, engagement and acceptance of pilot site occupants and stakeholders, b) involve end users in the requirements definition activities of the project, c) training users and contributing to the adoption of the MOEEBIUS concept and operation in the pilot sites of the project, d) involving all stakeholders in the evaluation of MOEEBIUS results.

MOEEBIUS partners seek individual opportunities for further dissemination of project results and also should support each other collectively in specific activities dedicated to the good promotion of common achievements. Through the exploitation of various mainstream communication channels and the attraction of additional societal groups in the MOEEBIUS tangible results, the consortium will further attempt to increase awareness and enhance societal perception on how Research and Innovation can tackle emerging challenges and positively impact the society, while increasing visibility and information flow on the vital role of H2020 and EU funded research in realizing and achieving ambitious EU-wide societal, economic and sustainable growth goals.
Considering the capabilities offered by the technological components introduced in the project and the high replication potential of the solutions, relevant environmental, social and economic improvements are addressed:

As regards to the environmental impact, MOEEBIUS reduces the gap between energy prediction and real/measured energy performance of buildings to values below 10%, achieve energy demand reductions of 32%, reduce energy peak-demand at least 28%, and reduce unscheduled maintenance or corrective actions above 50%. Given the energy mix in the pilot countries of MOEEBIUS and consumption data of the pilot buildings, the foreseen peak and overall demand reduction enable large GHG emissions savings on an annual basis and increased integration of intermittent and fluctuating energy sources.

The expected social impact is mainly linked to the direct high level jobs and indirect jobs through EPC deployment and adoption of the business role of Demand Side Aggregators, the enhancement of customer confidence regarding EPC effectiveness, as well as the improvement of the quality of life of citizens satisfying occupants’ comfort, health and safety needs, while enabling significant energy savings.

Finally the economic impact of the project is addressed through the economic saving associated to reduction of energy consumption, economic growth due to new activity and indirect benefits as transforming consumers from passive stakeholders to dynamic bidirectional aggregated entities able to generate, store and manage diverse value streams. The holistic open approach to building control and monitoring systems allows the European Cleanweb Start-up and SME ecosystem to develop their innovative applications on top of the MOEEBIUS developments.
Mafra Town Hall, part of MOEEBIUS Portuguese pilot site
Components of MOEEBIUS NOD
Examples of developed Building Energy Models for the MOEEBIUS pilot sites
KUBIK test area for MOEEBIUS
Details of KUBIK building and available systems
MOEEBIUS framework and individual components workflow
Project dissemination poster
Moorhouse, part of MOEEBIUS UK pilot site
Stepa Stepanovic Primary School, part of MOEEBIUS Serbian pilot site