Abstract
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.
Highlights
As stated by the Energy 2020 strategy, the reduction of Greenhouse Gas (GHG) emissions in the European Union (EU) can only be achieved if tackling appropriate the big potential existing when increasing energy efficiency [1]
The optimisation process occurs in a loop where new scenarios are generated and evaluated and scenarios and their evaluation in terms of the cost and benefit functions [25]
The platform introduced in this paper offers a tool to stakeholders in order to support them during the decision-making to design energy efficient retrofitting projects at district scale
Summary
As stated by the Energy 2020 strategy, the reduction of Greenhouse Gas (GHG) emissions in the European Union (EU) can only be achieved if tackling appropriate the big potential existing when increasing energy efficiency [1]. Apart from the issue of considering the buildings as part of a more complex system, there is a challenge on evaluating the parameters related to energy efficiency or sustainability, which are usually too focused on a very specific aspect such as “energy consumption” and ignore other relevant parameters and impacts [3]. This evaluation, which is carried out through the use of simulation tools, results in different levels of accuracy but generally “imply the generation of ad hoc simulation models” [4]. This process is always prone to human error— when creating the
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