Data driven tools to assess the location of photovoltaic facilities in urban areas

作者：

Highlights：

• Decision-making software for optimal photovoltaic location has been developed.

• A data-mining process to assess the software development was used.

• Evaluation of photovoltaic potential in large urban areas is automated.

• Features of this software include open-source, online availability and ease-of use.

• Roof characteristics in urban areas are automatically analysed.

摘要

•Decision-making software for optimal photovoltaic location has been developed.•A data-mining process to assess the software development was used.•Evaluation of photovoltaic potential in large urban areas is automated.•Features of this software include open-source, online availability and ease-of use.•Roof characteristics in urban areas are automatically analysed.

论文关键词：Renewable energy,Photovoltaic systems,LiDAR images,Semantic segmentation,Roof feature extraction,Energy forecast

论文评审过程：Received 17 May 2021, Revised 6 March 2022, Accepted 25 April 2022, Available online 5 May 2022, Version of Record 13 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117349