Data-driven decision-support to increase energy efficiency through renovation in European building stock.

Informacje na temat projektu

EERAdata

Identyfikator umowy o grant: 847101

DOI

10.3030/847101

Projekt został zamknięty

Data podpisania przez KE 25 Czerwca 2019

Data rozpoczęcia 1 Lipca 2019

Data zakończenia 28 Lutego 2022

Finansowanie w ramach

SOCIETAL CHALLENGES - Secure, clean and efficient energy

Koszt całkowity

€ 1 489 033,13

Wkład UE

€ 1 489 031,63

1 489 031,63

1,50

Koordynowany przez

TECHNISCHE UNIVERSITAET MUENCHEN
Germany

Periodic Reporting for period 2 - EERAdata (Data-driven decision-support to increase energy efficiency through renovation in European building stock.)

Okres sprawozdawczy: 2021-01-01 do 2022-02-28

Energy efficiency (EE) in the building sector is a core element of the European Union member states to be able to deliver on their Paris Agreement commitments. While energy standards for new constructions are gradually being raised, around 75% of the existing buildings deliver a poor energy performance, have questionable built quality as well as inadequate indoor environment. While the energy cost-saving effects through EE investments have been the subject of extensive research, the direct and indirect effects on society, environment and the economy are less defined and publicly acknowledged.

EERAdata demonstrates the wide range of benefits for society, the economy and the environment that building energy efficiency can achieve when implemented on a large scale and with a high sustainable standard. These long-term impacts, which are quantified and communicated to local decision-makers, can be sorted into the three pillars of sustainability:
Society: By reducing energy consumption and improving indoor climate significant benefits in occupant productivity, health, indoor climate and household finances can be generated.
Environment: 40% of all energy and material consumption and 36% of CO2 emissions in the European Union arise in private and public buildings. Buildings emit particulate matter, use land, water, etc. to be built, operated, and deconstructed. Making the Energy Efficiency first principle (EEfP) operational will reduce the impacts buildings have on the environment.
Economy: The construction sector provides 18 million direct jobs in the EU member states and contributes to about 9% of the EU's GDP. Up to 95% of construction, and architecture firms are small and medium-sized enterprises which are mainly located in municipalities and regions that EERAdata focuses on. The public investment in EE in buildings can be a significant stimulus for the local economy and increase innovation and knowledge within companies.

The EERAdata project’s main objective therefore is to contribute to the understanding and operationalisation of the EEfP by developing a methodology and a software tool to assess the multiple benefits of EE investment in the building stock on a social, economic, and environmental scale. It furthermore expands existing decision-making processes and policies and improves building EE projects.

The project started with an extensive online survey, several interviews, and bilateral workshops with the implementing partners, to create a baseline over the availability of building stock and social data, existing EE policies and processes.

The science team developed 5 interconnected assessment modules, which assess and quantify the multiple benefits that are induced by building energy efficiency. Their outputs can directly support decision making processes with enhanced information on the socio-economic and environmental effects of building improvements. The modelling took place in these areas: energy consumption, life-cycle assessment, indoor-climate assessment, socio-economic assessment, supply-side infrastructure. These newly developed methodologies have been combined with a complex data management system for local and regional building data. Results were integrated into a stand-alone software application which provides insights for planners and decision makers. Around 400 parameters and indicators have been integrated, and were populated with scientific data as well as real, location and building specific data from practical partners in 5 countries: Spain, Denmark, Slovenia, Poland and Germany.

The team designed a highly flexible software architecture in which building and global parameters can be adjusted with local data from any place in the EU to create a unique software application solely for a particular location. The system processes data from the real building stock of practical partners as well as from a scientific and statistical knowledge base, compensating for potential data gaps and modelling needs. Framed by the data management plan, the consortium has defined around 449 parameters (building characteristics, building technology, weather data, occupant data, statistics, etc.) which represent specific buildings and their local environment.

To create a solution which is tailored to the needs of its users, the project team established three regional networks for testing and validation to see the functionality of the tool in different case studies. Additionally bilateral trainings were performed to engage stakeholders like energy agencies, cities, social housing agencies, etc. which would use the decision support tool to estimate the wider benefits of their building development strategies.

In March 2020, due to COVID-19, some project workflows had to be changed into an agile structure, which improved the depth of the models but extended the overall development progress. Physical meetings have been moved to online collaboration. Since then, multiple stakeholder events, including showcases for the software, training and technical webinars have been conducted online. A hybrid final conference in December 2021 marked the end of the project, enhanced by a public tutorial during the project extension in February 2022.

The project is visibly active through its website and on social media and EERAdata findings are shared on Twitter and LinkedIn. EERAdata published its first video on Vimeo in M7 followed by a second one in M30, webinars, tutorial and explanation videos, which show the different features of the DST, on the project’s YouTube channel. A core element of the dissemination strategy of EERAdata is the newsletter, which has been sent out to the project partners and the stakeholder network regularly. In December 2020, the consortium benefited from the EC’s Exploitation Booster Service and participated in a two-day workshop to elaborate on the key exploitable results of the project.

EERAdata progresses beyond the state of the art by being the first project that combines the socio-economic and environmental assessment of EE impacts on building level in one decision support tool, tailored to the specific needs of municipalities and regions. The methodology and data collection processes consolidate the evidence of the multiple benefits of EE investments in buildings while providing a way to make this evidence meaningful and accessible to regional and municipal authorities involved in the delivery of EE projects. It enhances arguments for energy efficient and sustainable buildings in both the political and the planning process.

Other than existing databases or studies, EERAdata focuses on the on-site challenges and combines real data with knowledge and models from scientific sources. It raises awareness of the multiple benefits of EE from single buildings to full cities and serves as a tool, even for smaller municipalities, to provide the right arguments to create sustainable long-term strategies for their building stock. The developed software solution is moreover fully flexible and can be adapted entirely to the situation of a potential use case.

The project benefits from having the future users within the developing team, accompanying every step in the design, and assuring that the outcome can be integrated into the everyday processes and tasks. EERAdata thus provides a bottom-up approach to integrate the goals of directives like the EPBD or EED directly into practice.

Figure 1: the overall objectives of EERAdata

Figure 3: the data management logic of the EERAdata DST

Figure 2: the five assessment modules of the EERAdata decision-support tool

Figure 4: the EERAdata DST frontend and backend

Periodic Reporting for period 2 - EERAdata (Data-driven decision-support to increase energy efficiency through renovation in European building stock.)

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