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.


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    Titel :

    PV Power Prediction Based on XGBoost Algorithm


    Beteiligte:
    Hong, Yufan (Autor:in) / Yang, Jingxian (Autor:in) / Yang, Zhen (Autor:in) / Yan, Jing (Autor:in)


    Erscheinungsdatum :

    11.10.2023


    Format / Umfang :

    2654149 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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