摘要
风电历史数据的正确性对于风电预测的精确度有很大的影响,然而由于风电具有较大的波动性,且周期性不明显,常规的判断方法无法找出其中存在的不良数据。将风电功率数据中的不良数据看成奇异点,提出了基于小波奇异性检测原理的检测不良数据的方法,并用实例说明了该方法的有效性。
The correctness of the historical data for wind power is essential to the precision accuracy ofwind power forecast. Given the large volatility with nolacking of obvious periodicity, routine methods cannoffails to find out identify the bad data in the forecast. The current paper regards the bad data of the wind power data as singular points, and proposes the new detecting methods are proposed based on the wavelet singularity detection principle. Examples are also included to demonstrate the effectivenesss of the proposed method.
出处
《电网与清洁能源》
2010年第6期67-71,80,共6页
Power System and Clean Energy
关键词
风电预测
小波奇异性检测
模极大值
wind power forecasting
wavelet singularity detecting
module maximum
