This is accompanies code of Appendix B in paper “Ham, S.-W., Karava, P., Bilionis, I., and Braun, J. (2020). Real-time model for unit-level heating and cooling energy prediction in multi-family residential housing for eco-feedback design. Submitted to Journal of Building Performance Simulation.”. This is a simple demonstaration of Liu-West filter for a simple building gray-box model. We generated a synthetic data and applied Liu-West filter to see if the filter can be applicable for this problem. All code is written in R language. The main purpose of this document is to provide reproducible example.
The pacakge depedency of this code is managed by renv package. You can look at renv.lock file to see the required package. However, for the simplicity, just run following script on this rproject.
After clone the repository and run building_lw_filter.Rproj file (you must have Rstudio) with R>3.5.3.
git clone https://github.com/ecosang/building_lw_filter.git
In R console, run following script.
# Run this code in Rstudio
install.packages('renv',repos="https://cran.rstudio.com")
renv::equip() #install required software
renv::restore()Technically, this installs all required packages, and you can reproduce all codes below. However, if this doesn’t work, please report issues.
All functions used in this code is in code/utility.R. Also, all generated data and trained model are stored in data folder.
Render notebook
#with .Rproj . install pandoc >2.9
rmarkdown::render(input='code/liu_west_filter_for_a_building_grey_box_model.Rmd',
output_file = '../docs/filter.html')