Many studies have investigated different aspects in the decarbonisation of the European housing stock. However, a comprehensive quantitative analysis of the literature on the diffusion of energy efficiency technologies is still missing. We conducted a bibliometric analysis to better understand the knowledge base in the field energy efficiency technology diffusion in the European residential building stock. After the scanning and screening process, we identified 954 scientific articles pertinent to this topic. Through a co-citation network analysis, we generated a visual knowledge structure of the field and by the further investigation of the bibliography we were able to synthesize the state-of-the-art and answer to our initial research questions. Results of the co-citation network show a scattered and fragmented field in many domains. The descriptive analysis highlights this fragmentation, especially on a cross-country level among EU country members. Findings from this study contribute to map the scientific knowledge base in relation to technology diffusion in European residential building projects, identify relevant topic areas, visualize the links between the topics, as well as to recognize research gaps and opportunities. The methodology utilized in this paper proved to be viable approach to map and characterize the knowledge base within a field and can, therefore, be replicated in upcoming studies with analogous ambitions.

The HoEff-CIM-project aims at developing automated inventory and evaluation tools, which support portfolio managers to plan and perform energy efficiency measures within large properties, considering their highly heterogeneous usages and structural specifications. The project covers models and tools, which facilitate the assessment of existing building stocks and the recognition of state of the art energetic reliance and renovation concepts. These concepts are then automatically adapted to different structural, technical and usage dependent parameters. The tools will help to analyse building physics and building services but also to empower strategic planning and energy distribution schemes. Therefore, an intuitive dataflow was needed that streamlines the process from data acquisition (building inspection), evaluation of buildings and renovation measures to the elaboration of specific building energy reports; all resulting in master plans for building complexes as well as systematic renovation strategies for larger properties. Particular emphasis was put on the determination of joint influences of building construction and building services on potential energy savings. Accompanying this quantification process, uncertainty and sensitivity analyses have been performed via Bayesian Network theory and statistical analytics. Different renovation concepts have been analysed, modelled and evaluated regarding their energy saving potential, usability as well as ecologic features. A ranking system was developed to assess specific energy demands of different building usages and to identify the most effective renovation measures. The result is a fully transparent, interactive and easy to understand decision-making methodology. The holistic approach contributes to create climate neutral building stocks and consequently to reach the energy saving and environmental goals defined by national and international governmental institutions (e.g. EED).