ShuhuaGao / PV-PPSO

Highly efficient photovoltaic parameter estimation using parallel particle swarm optimization on a GPU

PV-PPSO

Code for the paper: Highly efficient photovoltaic parameter estimation using parallel particle swarm optimization on a GPU. Accepted by the 30th International Symposium on Industrial Electronics (ISIE), held 20-23 June 2021 in Kyoto, Japan.

View files

You can view the notebook files in the notebook directory online.

How to run

Install Julia (if not yet)

This code is implemented with the Julia programming language. Please first install Julia. We worked with Julia v1.6.0-rc1, but other versions like v1.5.3 and higher versions should also work.

Run the code with the steps below

1. Download or clone this repository to your local machine.
2. Launch Julia REPL from the repository directory, which has been installed automatically during Julia installation.
3. In Julia REPL:
   • type ] to enter package mode
   • type activate . to activate the current environment of PV-PPSO
   • type instantiate to install required packages of current project
   • press backspace until leaving the package mode
4. Type the following in the Julia REPL to start Jupyter notebook for Julia (documentation)

   using IJulia
   notebook(dir=pwd())

5. In the Jupyter notebook shown in your browser, go into the notebook subfolder to run notebooks.

How to cite

@INPROCEEDINGS{Gao-Highly,  
author={Gao, Shuhua and Xiang, Cheng and Lee, Tong Heng},  
booktitle={2021 IEEE 30th International Symposium on Industrial Electronics (ISIE)},   
title={Highly efficient photovoltaic parameter estimation using parallel particle swarm optimization on a GPU},   
year={2021},  
volume={},  
number={},  
pages={1-7},  
doi={10.1109/ISIE45552.2021.9576495}
}