基于濾波技術的上海日最大電力負荷氣象預報模型
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國家自然科學基金項目(41275021)、上海市氣象局研究型科技專項(YJ201302)資助


Meteorological Forecast Model of Daily Maximum Electrical Load in Shanghai Based on Filter Technique
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    摘要:

    電力負荷與氣象條件密切相關,為建立上海市日最大電力負荷的預報模型,利用2010—2013年上海市日最大電力負荷數據及同期氣象資料,分析日最大電力負荷的時間變化特征及其與氣象因子的相關性,并基于濾波技術將日最大電力負荷分離為時間趨勢項和逐日變化項,用逐步回歸方法針對冬季和夏季分別建立預測模型。結果表明:①上海日最大電力負荷的各個節假日效應存在差異,春節節假日效應持續時間最長,影響最大,國慶節假期前半段節假日效應明顯大于后半段。夏季的周末效應最強。②采用逐步回歸方法建立的氣象預報模型效果較好,回代年和預測年的平均預測相對誤差均小于5%。

    Abstract:

    Electrical load is significantly impacted by weather conditions. Therefore, the seasonal variation, holiday effects, weekend effects, and the weather dependency of daily maximum electrical load are investigated by using the daily maximum electrical load data in Shanghai and meteorological observations from the Xujiahui weather station from May 2010 to December 2013. The stepwise regression method and filter technique are employed to build the meteorological forecast model in winter and summer. The model consists of two components: regular change component and weathersensitive component. The results show that the effects of various holidays are different. The Spring Festival has the longest and greatest influence on daily maximum power load. The holiday effect is more pronounced during the first several days of the National Day than in the other days. The weekend effect is greater in summer than in other seasons. The best model is able to explain most of variability in daily maximum electrical load, with the mean prediction relative error less than 5%.

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傅新姝,談建國.基于濾波技術的上海日最大電力負荷氣象預報模型[J].氣象科技,2015,43(6):1209~1212

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  • 收稿日期:2014-10-20
  • 定稿日期:2015-07-27
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  • 在線發布日期: 2015-12-29
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