Current climate change threats and increasing CO₂ emissions, especially from the building stock, represent a context where action is required. It is necessary to provide efficient manners to manage energy demand in buildings and contribute to a decarbonised future. By combining new technologies, such as artificial intelligence, Internet of things, blockchain, and the exploitation of big data towards solving real life problems, the way could be paved towards smart and energy-aware buildings. In this context, the aim of this paper is to present a critical review and an in-detail definition of the big data value chain for the built environment in Europe, covering multiple needs and perspectives: “policy”, “technology” and “business”, in order to explore the main challenges and opportunities in this area.

Energy-efficient retrofitting of buildings has become essential to achieve the environmental objectives of the European Union’s (EU) strategies towards reducing carbon emissions and energy dependency on fossil fuels. When tackling retrofitting projects, the issue of scale becomes essential as sometimes this can determine the sustainability of the project. Therefore, a comprehensive approach is essential to ensure effective decision-making. A platform has been designed within the EU funded OptEEmAL project to support stakeholders in this process, providing functionalities that can automatically model and evaluate candidate retrofitting alternatives considering their priorities, targets and boundary conditions. A core element of this platform is the evaluation framework deployed which implements a multi-criteria decision-making approach to transform the priorities of stakeholders into quantifiable weights used to compare the alternatives. As a result, more informed decisions can be made by the stakeholders through a comprehensive evaluation of the candidate retrofitting scenarios. This paper presents the approach followed to develop and integrate this evaluation framework within the platform as well as its validation in a controlled environment to ensure its effectiveness.

The design of district and urban energy efficient retrofitting projects is a major challenge if contrasted solutions want to be implemented. From the establishment of the criteria to the calculation of indicators, there are several aspects to be considered, such as evaluating a series of refurbishment solutions or establishing an adequate method to select the optimal solution. Apart from this process requiring a high number of time and resources, it can result in a number of inaccuracies, leading to inadequate decisions or designs. The main achievement of the BRIOTOOL solution proposed is the transformation of a subjective problem (what the best combination of energy conservation measures to implement is) into a mathematical problem, which ensures a more robust decision-making process. In particular, by analysing which multi-objective optimization method (NSGA-II, IHS, MHACO or NSPSO) is the most appropriate, based on execution time, number of different and optimal solutions, and hypervolume of the Pareto front generated. As a result, the time reduction and the increase in the accuracy of the process compared to business as usual practices shows the benefits of the solution in designing energy efficient retrofitting projects at district level.

The EU strategies to reduce carbon dioxide emissions highlight the importance of renovating the existing building stock. It is one of the most contributing sectors to these undesired emissions to the atmosphere. The business-as-usual practices for designing energy-efficient retrofitting projects are still too time consuming and imprecise, and their supporting tools are not interconnected, provoking a lack of trust within the sector, particularly from investors. There is a need to improve these practices by reducing the errors and the time required to evaluate retrofitting alternatives to select the most appropriate according to the stakeholders’ priorities. To address this gap, the Optimised Energy Efficient Design Platform for Refurbishment at District Level (OptEEmAL) solution enables the automatic generation of scenarios of energy conservation measures and their simulation and optimisation, based on data provided by the users. This solution automatically launches and connects the processes that the different stakeholders usually carry out in a long period of time. This allows testing a more varied set of solutions and engages stakeholders along the process supported by the integrated project delivery approach. As a result, time is reduced, as well as errors and, therefore, costs, which will lead to increase in efficiency and confidence among stakeholders.

The implementation of energy policies to reduce CO₂ emissions poses specific challenges, especially to public authorities, who should define specific objectives, and evaluate the adequacy and impact of energy actions proposed. Nevertheless, an appropriate analysis is highly time-consuming due to the lack of tools. In this process, the first step is to establish the baseline energy status of the area of study. Only with this knowledge, in particular of the residential sector (main CO₂ emissions contributor in cities), is it possible to plan for a low carbon economy. In this context, the ENERGIS tool will support energy planners by mapping energy demand of the residential sector at different scales, as a first step towards CO₂ emissions calculation. To do so, a nationally validated Energy Performance Certification (EPC) tool has been automated, its results at building level mapped and aggregated at different scales. By basing the proposed platform on EPC calculation methodologies supported by the Energy Performance Directive of Buildings (EPBD 2010/31/EU), the ENERGIS platform achieves two main goals: it aids in the implementation of energy directives and energy actions by offering an easy to use tool to identify areas in need and, secondly, it promotes the EPBD, by making use of one of its main instruments to measure energy performance: the EPCs.