Treffer: Investigation and application of big data and AI-Powered provincial power grid accurate planning support platform.

Title:
Investigation and application of big data and AI-Powered provincial power grid accurate planning support platform.
Source:
Australian Journal of Electrical & Electronic Engineering; Dec2025, Vol. 22 Issue 4, p696-706, 11p
Database:
Complementary Index

Weitere Informationen

This study presents an accurate planning assistance platform for big data and artificial intelligence-based provincial power grids. The platform greatly increases the efficiency of data integration and management by building a planning big database containing fundamental geographic information, thematic data, remote sensing image data, and planning business data. Technically speaking, this paper addresses the issues of accuracy and speed in the processing of remote sensing image data by using deep learning algorithms like convolutional neural networks (CNN) and full convolutional neural networks (FCN) to achieve automatic classification of high-resolution optical remote sensing images and residential area extraction. In the meantime, the intelligent routing approach, which is based on cost surface modelling and multi-criteria decision-making, optimises the routing of power lines by carefully taking into account a wide range of variables, including land use, accessibility for vehicles, and environmental impact. In addition to resolving the primary issues with present power grid planning, this study's exact planning support platform for provincial power grids greatly enhances real-time, accurate, and scientific planning. [ABSTRACT FROM AUTHOR]

Copyright of Australian Journal of Electrical & Electronic Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)