With the rapid development of renewable energy, the promotion and deployment of photovoltaic (PV) power stations are gradually advancing. However, the output of photovoltaic power generation is greatly affected by the meteorological condition, and the utilization of solar energy remains challenging due to its strong stochastic nature. Accurate PV power prediction is a way to solve this problem. Firstly, the paper proposes a PV power forecasting method based on XGBoost algorithm. Then, the PV power prediction model is built and the evaluation indicators of forecasting performance are proposed. Finally, a case study is used to verify the effectiveness of the proposed method.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    PV Power Prediction Based on XGBoost Algorithm


    Contributors:
    Hong, Yufan (author) / Yang, Jingxian (author) / Yang, Zhen (author) / Yan, Jing (author)


    Publication date :

    2023-10-11


    Size :

    2654149 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Ship body local vibration prediction method based on SA-XGBOOST algorithm

    BAI ZHIYANG / SHI ZHONGHUA / HONG WANG et al. | European Patent Office | 2025

    Free access



    Traffic accident prediction system based on Ada-XGBoost

    CHANG RUNQI | European Patent Office | 2021

    Free access