Parametric energy performance analysis and monitoring of buildings—HEART project platform case study

•Deep refurbishment of buildings to nZEB standards is an open challenge.•Design optimization is a resource intensive process requiring appropriate training.•A gap between simulated and measured performance is frequently found in high performance buildings.•HEART project platform aims to address relevant issues, from design to operation.•Parametric performance analysis and model calibration are integrated in this study. Building performance analysis changed the way in which buildings are designed and operated. The evaluation of different design and operation options is becoming more resource intensive than ever before. Although building dynamic simulation tools are potentially a suitable way for assessing energy performance of buildings accurately, they require adequate training and a careful evaluation of model input data. In Europe, the majority of buildings were constructed before 1990 and are in urgent need for a significant energy efficiency improvement, through deep renovation. In this respect, advanced renovation solutions are available, but costly and lengthy renovation processes and technical complexities hinder the achievement of a large scale impact. Energy refurbishment of buildings is an open challenge and essentially requires the adoption of a valid methodological approach to link design and operational performance analysis transparently, in order to address the potential gap between simulated and measured results. The HEART project, funded in the EU Horizon 2020 program, aims to address the increasing need for deep retrofit interventions and to develop systemic strategies leading to high performance and cost effective solutions. The research for the cloud platform used in the project is based on two fundamental tools: parametric simulation to produce a large spectrum of possible building energy performance outcomes (considering realistically the impact of the user behaviour and variable operating conditions from the very beginning), and model calibration employing simple, robust and scalable techniques. In this paper we present the preliminary development and testing of the computational processes that will be implemented in the cloud platform, employing the first pilot case study of HEART Project in Italy, currently under refurbishment.