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Research Article

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

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  • @ARTICLE{10.4108/ew.5487,
        author={Jun Zhang and Huakun QUE and Xiashan Feng and Xiaofeng Feng and Xiling Tang},
        title={Research on Improvement Calculation Method of Grid Power Losses Based on New Energy Access Model},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={11},
        number={1},
        publisher={EAI},
        journal_a={EW},
        year={2024},
        month={12},
        keywords={distribution grid, random forest, AMDs, optimizaion model, power flow},
        doi={10.4108/ew.5487}
    }
    
  • Jun Zhang
    Huakun QUE
    Xiashan Feng
    Xiaofeng Feng
    Xiling Tang
    Year: 2024
    Research on Improvement Calculation Method of Grid Power Losses Based on New Energy Access Model
    EW
    EAI
    DOI: 10.4108/ew.5487
Jun Zhang1,*, Huakun QUE1,*, Xiashan Feng2,*, Xiaofeng Feng1,*, Xiling Tang1,*
  • 1: Metrology Center of Guangdong Power Grid Corporation, Guangdong Power Grid New Energy Application Research and Development Technology Park, No. 9 Meilinhu Road, Shijiao Town, Qingcheng District, Qingyuan City, Guangdong Province, 511545, China
  • 2: Zhanjiang Power Supply Bureau of Guangdong Power Grid Co., Ltd, Power Supply Service Center, No. 37 South Haibin Avenue, Xiashan District, Zhanjiang City, Guangdong Province, 524100; China
*Contact email: luoliny2020@163.com, luoliny2020@163.com, luoliny2020@163.com, luoliny2020@163.com, luoliny2020@163.com

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.

Keywords
distribution grid, random forest, AMDs, optimizaion model, power flow
Received
2024-12-04
Accepted
2024-12-04
Published
2024-12-04
Publisher
EAI
http://dx.doi.org/10.4108/ew.5487

Copyright © 2024 Zhang et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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