Paper details

Title: Optimizing Electric Vehicle Charging Schedules Based on Probabilistic Forecast of Individual Mobility

Authors: Haojun Cai, Yanan Xin, Henry Martin, Martin Raubal

Abstract: Obtained from abstractsource

CODECHECK details

Certificate identifier: 2022-003

Codechecker name: Carlos Granell

Time of check: 2022-07-09 12:00:00

Repository: https://osf.io/JDTN3

Full certificate: https://doi.org/10.17605/OSF.IO/JDTN3

Type: conference

Venue: AGILEGIS

Summary:

The authors included a link to an anonymous GitHb repository containing detailed instructions and an entry point (main script) to run the entire analysis. The authors claimed that input data cannot be disclosed. They provided me a few synthetic input samples (CSV format) to run the probabilistic models and charging strategies for simulation and evaluation, so there are differences between the results of the reproduction and the ones in the original paper. The reproduction described in this report uses the Python code provided. Even though the reproduction exercise with synthetic data failed during the last step of the script, I consider the paper was partially reproducible based on the synthetic data.

Cite this certificate: Citation metadata retrieved from data.crosscite.org

Loading citation…
Copied!

View certificate data as JSON

https://codecheck.org.uk/ | codecheckers | Zenodo Community

© team@cdchck.science | Published under CC BY-SA 4.0

DOI of Zenodo Deposit

CODECHECK is a process for independent execution of computations underlying scholarly research articles.