Data for "Evaluating single-zone grey-box thermal models: Impact of model structure on prediction accuracy and computational cost"
Abstract
This data repository provides the datasets for the research paper, "Evaluating Single-Zone Grey-Box Thermal Models: Impact of Model Structure on Prediction Accuracy and Computational Cost". The study systematically compares low-order grey-box RC model structures using high-fidelity synthetic data across multiple BESTEST/BOPTEST scenarios and climates, quantifying the trade-offs between prediction accuracy and computational time.This repository includes two main folders of the simulation results and figure's data.exported_rawdata/ — performance indices from the simulations of the identified grey-box RC models: These datasets include the key performance indices such as RMSE and computation time for the combined and separated case scenarios.exported_figdata/ — processed data to reproduce all figures: These datasets are the processed data tables used for regenerating the figures in the manuscripts.
Fields of Study & Subjects
Building Energy and Comfort Optimization
Integrated Energy Systems Optimization
Building energy efficiency and sustainability
Publication details
- Journal / source
- University College London
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Dataset