Optimization of energy-saving retrofit solutions for existing buildings : a multidimensional data fusion approach

Abstract

Older buildings often exhibit multiple problems, such as high energy consumption, high carbon emissions, and outdated performance. To achieve optimal decision-making for the energy efficiency retrofitting of existing buildings, a data fusion-based hybrid multicriteria decision-making method based on an extension-based trapezoidal cloud model (TCM), and a multidimensional renovation program evaluation index system including technical, safety, economic, and environmental applicability is proposed. The validity and applicability of the model is verified using an old building renovation as an example. The results indicate that (1) incorporating technical, safety, economic, and environmental suitability factors will enable future of building retrofitting to focus on sustainability. None of the current retrofit programs can economically cover the costs they incur through their energy saving benefits, which will not motivate owners to complete retrofitting and requires joint efforts between the government and the building industry to improve the sustainability of existing buildings. (2) Building retrofitting programs should primarily prioritize technical and economic applicability, which exhibit importance values of 0.2930 and 0.2496, respectively. (3) The stability of the retrofit effect is the primary reason for variations in the effectiveness of selected programs. A program with a greater degree of affiliation with levels I, II, and III of the index is more stable and less prone to deterioration than other programs. The proposed method provides an efficient decision-making tool for the selection of retrofit programs for existing buildings and is suitable for popularization and application, thus promoting building energy conservation, emission reduction and sustainable development.