Analysis of synergistic influence of multi-scale design parameters on nearly-zero energy office blocks performance based on architectural morphological classification and parametric modeling

Design parameters at different scales in the pre-design phase could significantly impact both building energy consumption and photovoltaic (PV) power generation potential. However, existing studies often overlook the synergistic effects of design parameters across multiple scales (block-building-facade scales) when evaluating these aspects. This paper aims to propose a workflow for the assessing building energy consumption and PV power generation potential of office blocks applicable in the pre-schematic design phase considering the synergistic influence of multi-scale design parameters, using building typology and parametric modelling approach. The study proposed a multi-scale design parameter classification system combined with parametric modelling. The study investigated 80 office blocks in Wuhan as the study case, which were classified into array type and enclosed type. Correlation analysis and multiple regression equations were used to quantify the single versus synergistic effects of different scale design parameters. Results suggest that focusing solely on a single scale during the pre-design stage is typically inadequate for understanding building energy potential. In contrast, multi-scale synergistic analysis boosts energy use intensity (EUI) by 7.56% and net energy use intensity (NEUI) by 33.96%. Under multi-scale synergistic conditions, the EUI of array type is more influenced by the building design parameters, while the NEUI is effected by the balance of multi-scales design parameters. While the EUI of enclosed types exhibit balanced effects across multi-scale design parameters, with NEUI results aligning closely with PV power generation potential. Multiple regression equations highlight building density and shape factor as key influencers for both array and enclosure layouts. This study offers designers a flexible and scalable workflow for evaluating building energy consumption and PV power generation potential in the pre-design phase. The findings can guide nearly-zero energy urban block planning to achieve a balance between energy supply and demand.