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          Suzhou Electric Appliance Research Institute
          期刊號: CN32-1800/TM| ISSN1007-3175

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          風電功率及其預測誤差概率分布研究

          來源:電工電氣發布時間:2021-09-18 13:18 瀏覽次數:28

          風電功率及其預測誤差概率分布研究

          謝彥祥
          (中國電力工程顧問集團西南電力設計院有限公司,四川 成都 610021)
           
              摘 要:進行風電功率及其預測誤差概率分布研究對分析風電功率分布特性有重要意義。以風電功率、日功率波動量均值為指標,統計分析風電在不同時間尺度下的波動概率分布;針對正態分布模 型對風電功率及其預測誤差分布擬合效果較差問題,利用非參數估計法擬合風電功率及其短期預測誤差概率分布,并以殘差平方和、相關系數為評價指標,對比不同預測模型和采樣間隔對應的擬合效果;基于實測數據的分析結果表明,非參數估計法可以有效擬合風電功率及其短期預測誤差概率分布,且具有較好的實用性。
              關鍵詞:風電功率;概率分布;短期預測;預測誤差分布;非參數估計
              中圖分類號:TM614     文獻標識碼:A     文章編號:1007-3175(2021)09-0007-07
           
          Study on Probability Distribution of Wind Power and Its Forecasting Error
           
          XIE Yan-xiang
          (Southwest Electric Power Design Institute Co., Ltd. of CPECC, Chengdu 610021, China)
           
              Abstract: The investigation of the distribution of wind power and its prediction error probability is necessary. It has a significant meaning to the analysis of wind power distribution characteristics. In this paper, the average value of wind power and daily power fluctuations were used as indicators to statistically analyze the probability distribution of wind power fluctuations on different time scales. The normal distribution model has problems of poor-fitting effect on wind power and prediction error distribution. This study used a non-parametric estimation method to fit wind power and its short-term prediction error probability distribution. It also used the residual sum of squares and correlation coefficient as evaluation indicators to compare the fitting effects of different prediction models and sampling intervals. The analysis result based on the measured data shows that the non-parametric estimation method can effectively fit the probability distribution of wind power and its short-term forecast error, and it has well practicability.
              Key words: wind power; probability distribution; short-term forecast; forecast error distribution; non-parametric estimation
           
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