Energy classification of urban districts to map buildings and prioritize energy retrofit interventions: A novel fast tool

This paper introduces a new methodology designed to assess the energy performance of urban districts. By integrating building energy performance standards with automated spreadsheet tools, the study provides a framework for quickly analyzing urban energy certificates to identify key areas for energy efficiency improvements. The model considers several factors influencing thermal and energy performance, such as heat transfer through the building envelope, internal heat gains, and energy supply from HVAC systems during both heating and cooling seasons. By evaluating energy needs for heating, cooling, domestic hot water, lighting, and equipment, the methodology offers a comprehensive view of building energy consumption. The adaptable spreadsheet model generates various outputs based on factors like architectural features, expositions, systems for a total of 30 inputs. The tool, designed to be as simple as possible while still ensuring accurate predictions of the energy needs of the analyzed buildings, serves three main purposes. First, it speeds up the energy modeling process of buildings at various scales. Second, it provides a user-friendly system that anyone can use to calculate a building's energy needs and its corresponding energy class. Finally, it suggests optimization strategies by proposing refurbishment solutions for the targeted building stock. Future development includes incorporating this model into geographic information systems for spatial mapping of urban energy districts, offering useful insights for focused interventions and sustainable urban development. [Display omitted] •Comprehensive methodology for building energy efficiency tool development.•Aiming at sustainability goals for various building scale targets.•Validates tool against EnergyPlus simulations for accuracy.•Results show 5 % deviation in winter, 4 % in summer predictions.•Enhances confidence for urban energy planning decisions.