Quantifying the effects of different data streams on the calibration of building energy simulation

Introduction

This repository presents the documents and the code employed in our latest work "Quantifying the effects of different data streams on the calibration of building energy simulation". This study investigates and quantifies the impacts of inputs and outputs on Bayesian calibration performance of building energy modelling. It incorporates both single-output and multiple-output Bayesian calibration.

More details can be found in our paper:

Yaonan Gu, Wei Tian, Chao Song and Adrian Chong (2023). Quantifying the effects of different data streams on the calibration of building energy simulation. xxx, xx. doi: https://xx

Citation

Please cite this compendium as:

To be added xx

Key steps

The followings are the key steps to try the calibration process:

1. Download Energyplus (Version 9.1.0) Downlink.

2. Install the required Python packages.

3. Apply the code and other documents in this repository.

Install the required packages by using pip:

$ pip install -r requirements.txt

File structure

To be added 

Licenses

Code, Text and Figures : CC-BY-4.0