Paper Conference

Proceedings of Building Simulation 2021: 17th Conference of IBPSA

     

A knowledge-based framework for building model performance verification

Yan Chen, Jeremy Lerond, Xuechen Lei, Michael Rosenberg, Draguna Vrabie
Pacific Northwest National Laboratory, United States of America

DOI: https://doi.org/10.26868/25222708.2021.30725
Abstract: Building energy modeling (BEM) has been widely used by researchers, regulators, and engineers to quantify building energy performance. Quality assurance (QA) and quality control (QC) of model performance are essential parts of such an analysis. Currently, QA/QC is done in a manual and ad hoc manner, which is tedious, error-prone, and time-consuming when verifying a large number of models. To solve these challenges, we propose a dAta- driveN buIlding perforMance verificATion framEwork (ANIMATE), which conducts automated output-based verification of building operations requirements (especially for time-series output-based verification of control requirements). While this framework was developed for verifying energy model performance, it can be extended for other applications such as BEM software testing and performance verification of real buildings in the field.
Keywords: Simulation, Knowledgebase, Control performance verification, Quality control, Quality assurance
Pages: 1943 - 1950
Paper:
bs2021_30725