Data for "Evaluating single-zone grey-box thermal models: Impact of model structure on prediction accuracy and computational cost"

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.<code>exported_rawdata/</code> — 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.<code>exported_figdata/</code> — processed data to reproduce all figures: These datasets are the processed data tables used for regenerating the figures in the manuscripts.<br>