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Title

Research on Improvement Calculation Method of Grid Power Losses Based on New Energy Access Model.

Authors

Jun Zhang; Huakun QUE; Xiashan Feng; Xiaofeng Feng; Xiling Tang

Abstract

This research presents an improved calculation method for grid power losses, particularly focusing on the challenges posed by new energy access models. With the integration of electric vehicles and the rise of data centers, the demand for electrical energy has surged, leading to increased strain on grid stations and subsequent power losses. The proposed model aimed at reducing these power losses, while also examining existing systems to mitigate and analyze such issues. A significant contribution of this work is the application of the Random Forest machine learning algorithm, which enables efficient and accurate power flow calculations essential for optimizing grid performance. The proposed method is expected to enhance the grid's ability to handle future energy demands and contribute to the sustainable development of electrical energy systems.

Subjects

ELECTRIC vehicles; ELECTRIC power distribution; RANDOM forest algorithms; MACHINE learning; DATA libraries

Publication

EAI Endorsed Transactions on the Energy Web, 2024, Vol 11, Issue 1, p1

ISSN

2032-944X

Publication type

Academic Journal

DOI

10.4108/ew.5487

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