Joint Conditions Probability Forecast Method for Wind Speed and Wind Power
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摘要: 采用确定性预测模型对风速和风电功率进行预测,无法传递结果的概率可信程度,不适应风险分析与调控应用的需要。为此,建立了以当前时段实测风速和下一时段预报风速为联合条件的离散预报误差概率统计(forecast errorprobability distribution,FEPD)模型,并以该模型对未来时段的预报误差概率分布进行预测。首先由历史统计结果确定修正因子,利用风速波动分布特征(speed disturbanceprobability distribution,DPD)对预报误差概率分布进行偏度修正,再将修正后的预报误差概率分布与由确定性预测算法得到的结果相结合,从而得到风速概率性预测结果。实例表明,所提方法可以较好地预测未来时段风速及风电功率变化的概率分布结果。Abstract: Certainty forecast method could not meet the need of risk analysis and system operation because probability information was not included.This paper chose measured speed and forecast speed as joint conditions and made a discrete forecast error probability distribution（FEPD） model which could be used for next-time wind speed probability forecast.Firstly speed disturbance probability distribution（DPD） was adopted to modify skewness of FEPD with modification factor,then modified FEPD and certainty forecast value were combined to obtain wind speed probability distribution forecast result.DPD,FEPD and modification factor were all obtained from historical data with different statistical periods.In modification process,samples real-time scrolling technology was used to guarantee the distribution reasonable and promptly.Result shows that this model has a good effect when forecasting wind speed or power output probability distribution in next time range.
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