<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/10012241" mdate="2021-10-24 00:00:00"> <author>Yan Lyu and Yiqun Pan and Zhizhong Huang</author> <title>Geometric Simplification Method of Building Energy Model Based on Building Performance Simulation</title> <pages>440 - 445</pages> <year>2021</year> <volume>15</volume> <number>10</number> <journal>International Journal of Civil and Architectural Engineering</journal> <ee>https://publications.waset.org/pdf/10012241</ee> <url>https://publications.waset.org/vol/178</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESPr, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation the southward projected area and total side surface area of the building. Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that no more than 7 prediction error of annual coolingheating load will be caused by the geometric simplification for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.250.35, which means this method is applicable for building performance simulation.</abstract> <index>Open Science Index 178, 2021</index> </article>