A new era in the energy performance of buildings

Improving energy efficiency in buildings is a major priority for the European Union, yet current modelling processes do not accurately reflect consumption. The MOEEBIUS framework will provide the basis for more accurate energy performance assessment, underpinning efforts to improve efficiency and opening up new commercial opportunities, as Dawid Krysiński explainsH2020 680517 MOEEBIUS

Plotting a path to reduce the energy performance gap

Improving energy efficiency performance in buildings is a major priority for the European Commission, with a target of achieving 20 percent energy savings by 2020. The EU promotes solutions which reduce energy consumption in the building sector to achieve this, an area which forms the primary research focus for the MOEEBIUS projectH2020, MOEEBIUS, 68051

Energy, Environmental and Economic Analysis of Air-to-Air Heat Pumps as an Alternative to Heating Electrification in Europe

Heat pumps (HP) are an efficient alternative to non-electric heating systems (NEHS), being a cost-effective mean to support European building sector decarbonization. The paper studies HP and NEHS performance in residential buildings, under different climate conditions and energy tariffs, in six different European countries. Furthermore, a primary energy and environmental analysis is performed to evaluate if the use of HPs is more convenient than NEHS, based on different factors of the electric mix in each country. A specific HP model is developed considering the main physical phenomena occurring along its cycle. Open data from building, climatic and economic sources are used to feed the analysis. Ad hoc primary energy factors and greenhouse gas (GHG) emission coefficients are calculated for the selected countries. The costs and the environmental impact for both heating systems are then compared. The outcomes of the study suggest that, in highly fossil fuels dependent electricity mixes, the use of NEHS represents a more efficient decarbonization approach than HP, in spite of its higher efficiency. Additionally, the actual high price of the electric kWh hampers the use of HP in certain cases.European Commission's H202

HOLISDER Project: Introducing Residential and Tertiary Energy Consumers as Active Players in Energy Markets

Although it has been demonstrated that demand-side flexibility is possible, business application of residential and small tertiary demand response programs has been slow to develop. This paper presents a holistic demand response optimization framework that enables significant energy costs reduction for consumers. Moreover, buildings are introduced as main contributors to balance energy networks. The solution basis consists of a modular interoperability and data management framework that enables open standards-based communication along the demand response value chain. The solution is being validated in four large-scale pilot sites, which have diverse building types, energy systems and energy carriers. Furthermore, they offer diverse climatic conditions, and demographic and cultural characteristics to establish representative results.Research leading to these results has been supported by HOLISDER project. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 768614. The APC was funded by HOLISDER project

Engaging domestic users on demand response for heating cost reduction with a recommendation tool: Case study in Belgrade

[EN] The European Union has established a legislative framework that aims to enable consumers and businesses to take information-based decisions to save energy and money. Additionally, the increase of Distributed Energy Resources (both on generation and consumption) requires additional efforts to maintain the reliability and stability of the electric grid and the need of flexibility from residential buildings. The present study introduces a domestic decision support tool for reducing heating costs. This app provides detailed recommendations to end-users based on the day-ahead hourly weather forecast, electric and district heating tariffs predictions, heating demand, and heating systems dynamic performance. The tool was tested in 6 dwellings of a neighborhood of Belgrade during the last months of 2021 heating season (March-May). Energetic results suggest that 40% of participants followed the given recommendations and changed their heating pattern. Additionally, survey results show that end-users found the lack of information and knowledge as the main barrier to actively participate in the energy market, also preferring to have automatic control in their heating system. Authors conclude that recommendation tools are key elements in user-engagement, but they should be supported by additional information and training.Research leading to these results has been supported by HOLISDER project, Spain. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 768614. This paper reflects only the authors’ views and the Commission is not responsible for any use that may be made of the information contained therein

Energy Performance Assessment of Innovative Building Solutions Coming from Construction and Demolition Waste Materials

Prefabricated solutions incorporating thermal insulation are increasingly adopted as an energy conservation measure for building renovation. The InnoWEE European project developed three technologies from Construction and Demolition Waste (CDW) materials through a manufacturing process that supports the circular economy strategy of the European Union. Two of them consisted of geopolymer panels incorporated into an External Thermal Insulation Composite System (ETICS) and a ventilated façade. This study evaluates their thermal performance by means of monitoring data from three pilot case studies in Greece, Italy, and Romania, and calibrated building simulation models enabling the reliable prediction of energy savings in different climates and use scenarios. Results showed a reduction in energy demand for all demo buildings, with annual energy savings up to 25% after placing the novel insulation solutions. However, savings are highly dependent on weather conditions since the panels affect cooling and heating loads differently. Finally, a parametric assessment is performed to assess the impact of insulation thickness through an energy performance prediction and a cash flow analysis.This research was funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 723916 (Project H2020-EEB-2016 InnoWEE, G.A. 723916). This study reflects only the authors’ views and the Commission is not responsible for any use that may be made of the information contained therei

Simulation-Based Evaluation and Optimization of Control Strategies in Buildings

Over the last several years, a great amount of research work has been focused on the development of model predictive control techniques for the indoor climate control of buildings, but, despite the promising results, this technology is still not adopted by the industry. One of the main reasons for this is the increased cost associated with the development and calibration (or identification) of mathematical models of special structure used for predicting future states of the building. We propose a methodology to overcome this obstacle by replacing these hand-engineered mathematical models with a thermal simulation model of the building developed using detailed thermal simulation engines such as EnergyPlus. As designing better controllers requires interacting with the simulation model, a central part of our methodology is the control improvement (or optimisation) module, facilitating two simulation-based control improvement methodologies: one based in multi-criteria decision analysis methods and the other based on state-space identification of dynamical systems using Gaussian process models and reinforcement learning. We evaluate the proposed methodology in a set of simulation-based experiments using the thermal simulation model of a real building located in Portugal. Our results indicate that the proposed methodology could be a viable alternative to model predictive control-based supervisory control in buildings.Research leading to these results has been partially supported by the Modelling Optimization of Energy Efficiency in Buildings for Urban Sustainability (MOEEBIUS) project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 680517. Georgios Giannakis and Dimitrios Rovas gratefully acknowledge financial support from the European Commission H2020-EeB5-2015 project “Optimised Energy Efficient Design Platform for Refurbishment at District Level” under Contract #680676 (OptEEmAL). Georgios Kontes and Christopher Mutschler gratefully acknowledge financial support from the Federal Ministry of Education and Research of Germany in the framework of Machine Learning Forum (grant number 01IS17071). Georgios Kontes, Natalia Panagiotidou, Simone Steiger and Gunnar Gruen gratefully acknowledge use of the services and facilities of the Energie Campus Nürnberg. The APC was funded by MOEEBIUS project. This paper reflects only the authors’ views and the Commission is not responsible for any use that may be made of the information contained therein

Design of knowledge-based systems for automated deployment of building management services

Despite its high potential, the building's sector lags behind in reducing its energy demand. Tremendous savings can be achieved by deploying building management services during operation, however, the manual deployment of these services needs to be undertaken by experts and it is a tedious, time and cost consuming task. It requires detailed expert knowledge to match the diverse requirements of services with the present constellation of envelope, equipment and automation system in a target building. To enable the widespread deployment of these services, this knowledge-intensive task needs to be automated. Knowledge-based methods solve this task, however, their widespread adoption is hampered and solutions proposed in the past do not stick to basic principles of state of the art knowledge engineering methods. To fill this gap we present a novel methodological approach for the design of knowledge-based systems for the automated deployment of building management services. The approach covers the essential steps and best practices: (1) representation of terminological knowledge of a building and its systems based on well-established knowledge engineering methods; (2) representation and capturing of assertional knowledge on a real building portfolio based on open standards; and (3) use of the acquired knowledge for the automated deployment of building management services to increase the energy efficiency of buildings during operation. We validate the methodological approach by deploying it in a real-world large-scale European pilot on a diverse portfolio of buildings and a novel set of building management services. In addition, a novel ontology, which reuses and extends existing ontologies is presented.The authors would like to gratefully acknowledge the generous funding provided by the European Union’s Horizon 2020 research and innovation programme through the MOEEBIUS project under grant agreement No. 680517

Energy Performance Assessment of Innovative Building Solutions Coming from Construction and Demolition Waste Materials

Prefabricated solutions incorporating thermal insulation are increasingly adopted as an energy conservation measure for building renovation. The InnoWEE European project developed three technologies from Construction and Demolition Waste (CDW) materials through a manufacturing process that supports the circular economy strategy of the European Union. Two of them consisted of geopolymer panels incorporated into an External Thermal Insulation Composite System (ETICS) and a ventilated façade. This study evaluates their thermal performance by means of monitoring data from three pilot case studies in Greece, Italy, and Romania, and calibrated building simulation models enabling the reliable prediction of energy savings in different climates and use scenarios. Results showed a reduction in energy demand for all demo buildings, with annual energy savings up to 25% after placing the novel insulation solutions. However, savings are highly dependent on weather conditions since the panels affect cooling and heating loads differently. Finally, a parametric assessment is performed to assess the impact of insulation thickness through an energy performance prediction and a cash flow analysis

Simulation-based evaluation and optimization of control strategies in buildings

Summarization: Over the last several years, a great amount of research work has been focused on the development of model predictive control techniques for the indoor climate control of buildings, but, despite the promising results, this technology is still not adopted by the industry. One of the main reasons for this is the increased cost associated with the development and calibration (or identification) of mathematical models of special structure used for predicting future states of the building. We propose a methodology to overcome this obstacle by replacing these hand-engineered mathematical models with a thermal simulation model of the building developed using detailed thermal simulation engines such as EnergyPlus. As designing better controllers requires interacting with the simulation model, a central part of our methodology is the control improvement (or optimisation) module, facilitating two simulation-based control improvement methodologies: one based in multi-criteria decision analysis methods and the other based on state-space identification of dynamical systems using Gaussian process models and reinforcement learning. We evaluate the proposed methodology in a set of simulation-based experiments using the thermal simulation model of a real building located in Portugal. Our results indicate that the proposed methodology could be a viable alternative to model predictive control-based supervisory control in buildings.Παρουσιάστηκε στο: Energie