The evident need for improving the existing building stock still suffers from important barriers, such as the fragmentation of the value chain, the lack of information regarding some solutions, and the lack of confidence with respect to energy savings, which prevent unlocking investments, and the difficult communication among stakeholders. Therefore, new processes based on exploiting the potential of existing and new tools are required. In this framework, the OptEEmAL project has developed a tool that integrates stakeholders, data and tools in order to ease the process of designing energy efficient retrofitting projects at building and district scale. This tool works around an optimisation framework in order to evaluate, compare and optimise candidate retrofitting scenarios against a set of indicators showing the performance of the district. This evaluation and optimisation method is based on aggregating indicators through transforming the priorities of stakeholders into a mathematical weighting scheme, which makes it possible to provide scenarios within their expectations. Therefore, the generation of these scenarios is driven by their design parameters, being thus flexible and adapted to their needs. This paper shows the implementation of this tool and specifically 3 different prioritisation schemes, analysing how they impact into the decision making process and selection of the retrofitting strategy.Buildings account for approximately 40% of energy consumption and 36% of GHG emissions in the context of the EU [1]. When analysing the stock of existing buildings, around 30% of the building stock is more than 50 years old [2] and almost 75% is energy inefficient [3,4]. The implications of this energy inefficiency not only result in an energy and environmental cost, but also provoke other impacts, such as health problems due to the low levels of comfort within these buildings [5]. It is then imperative to focus on upgrading an ageing building stock, whose current renovation rates are low, at~1.2%. To achieve these targets, this rate should increase to 3% [6].On the other hand, the retrofitting market is quite fragmented, with multiple stakeholders with different and often conflicting interests. This is mirrored in the communication and information exchanges between them. This strong barrier is added to others, such as the lack of knowledge of some technologies among construction professionals, the varying ambition of performance requirements present within regulations, lack of awareness, and uncertainty as to the expected savings, which make

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.

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Designing energy retrofitting actions poses an elevated number of problems, as the definition of the baseline, selection of indicators to measure performance, modelling, setting objectives, etc. This is time-consuming and it can result in a number of inaccuracies, leading to inadequate decisions. While these problems are present at building level, they are multiplied at district level, where there are complex interactions to analyse, simulate and improve. OptEEmAL proposes a solution as a decision-support tool for the design of energy retrofitting projects at district level. Based on specific input data (IFC(s), CityGML, etc.), the platform will automatically simulate the baseline scenario and launch an optimisation process where a series of Energy Conservation Measures (ECMs) will be applied to this scenario. Its performance will be evaluated through a holistic set of indicators to obtain the best combination of ECMs that complies with user’s objectives. A great reduction in time and higher accuracy in the models are experienced, since they are automatically created and checked. A subjective problem is transformed into a mathematical problem; it simplifies it and ensures a more robust decision-making. This paper will present a case where the platform has been tested.

The EU strategies to reduce the carbon emissions highlight the importance of renovating the existing building stock as one of the major contributing sectors to these undesired emissions to the atmosphere. The existing practices to design energy efficient retrofitting projects are still too time consuming, unprecise and provoke, therefore, a lack of trust within the sector; especially to investors. There is a need to improve these practices through reducing the errors and the time required to evaluate retrofitting alternatives in order to select those most appropriate according to the stakeholders' priorities. In order to give an answer to this challenge, the EU funded project OptEEmAL has designed and deployed an integrated platform that delivers automatically some of the steps that belong to this process reducing thus time, errors and therefore costs, which will lead to increasing efficiency and creating confidence among the stakeholders.