Short-term power load forecasting based on improved Prophet algorithm
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(State Grid Hectric Reseerch Institute(NARI Group Corporation), Nanjing 211106, China)

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    Abstract:

    A new power load forecasting method based on optimized Prophet algorithm is presented. A power load time series can be disassembled into trend term, seasonal term and random term by Prophet algorithm. In the predicted time series, trend and seasonal term are predicted by Prophet, while the random term is replaced by the prediction output by XGBoost algorithm. The model proposed is easy to understand and requires only power load data, whose parameters can be adjusted by the analysts intuitively.The effectiveness of the forecasting method is proved by conducting experiments on the power load data obtained from power consumption information acquisition system. The result shows that the mean absolute percentage error of the forecasting result is reduced by up to 2.5% comparing with the original Prophet algorithm. At the same time, the root mean square error is reduced by up to 30.19%, which show its excellent improvement.

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刘涅煊,杨学良,陶晓峰,黄福兴,陆春艳.基于改进Prophet算法的短期日负荷预测方法研究[J].电力需求侧管理英文版,2022,24(5):58-63.

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History
  • Received:June 28,2022
  • Revised:July 26,2022
  • Adopted:
  • Online: September 27,2022
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