Combined time-varying forecast based on the proper scoring approach for wind power generation

Xingying Chen, Yu Jiang, Kun Yu, Yingchen Liao, Jun Xie, Qiuwei Wu

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    Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error distribution, a proper scoring approach is applied to combine plausible models to form an overall time-varying model for the next day forecasts, rather than weights-based combination. To validate the effectiveness of the proposed method, real data of 3 years were used for testing. Simulation results demonstrate that the proposed method improves the accuracy of overall forecasts, even compared with a numerical weather prediction.
    Original languageEnglish
    JournalThe Journal of Engineering
    Pages (from-to)67-72
    Publication statusPublished - 2017


    • Wind power plants
    • Power system planning and layout
    • Load forecasting
    • Mumerical weather prediction
    • Weights-based combination
    • Forecasting error distribution
    • Wind-power combined forecasts
    • Point forecasts
    • Wind power generation
    • Proper scoring approach
    • Combined time-varying forecasting


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