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PerformanceGap-Hybrid-Approach

Open source code of the paper:
A hybrid-model approach for reducing the performance gap in building energy forecasting
https://doi.org/10.1016/j.aei.2022.101627
Arxiv: http://arxiv.org/abs/2206.00460


Fig1

Fig6

Fig2

In the '3Y' folder, data is generated by simulations based on Level-of-Information (LOI) definition in the paper.

Table2

For running the code, please run notebook Run_model.ipynb

Additional python packages required:

  • sklearn
  • plotly
  • lightgbm

For using data & code for your production, please cite:

  • Chen, Xia, et al. "A hybrid-model forecasting framework for reducing the building energy performance gap." Advanced Engineering Informatics 52 (2022): 101627.
  • Xiao, Tong, Xu, Peng, Sha, Huajing, Chen, Zhe, & Gu, Jiefan. (2022). XuPengResearchGroup/EnergyDetective2020_dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6590976

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Open source code of paper: A hybrid-model approach for reducing the performance gap in building energy forecasting

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