利用空间相关性的超短期风速预测

发布时间：2018-02-09 11:55

  本文关键词： 风速预测 空间相关性 动态特征 离线分类建模 在线特征匹配　出处：《电力系统自动化》2017年12期 　论文类型：期刊论文

【摘要】：风速的空间相关性有助于提高其预测质量,特别是在风速突变的情况下。将"离线分类建模,在线匹配模型"的预测思路应用到利用空间相关性的超短期风速预测之中:通过历史数据的时序分析,识别其中各风电场风速存在空间相关性的时段;按其时序特征及其他的条件特征,将观察时窗内的风速序列划分为不同演化形态的样本子集;在离线环境下,分别根据各类形态的训练样本子集优化其专用的预测模型及参数;在线应用时,则根据当下窗口内风速序列的演化形态及相关的条件特征,按匹配所得模型及参数,根据参考风电场的实测数据预测目标风电场的风速。以实际的历史数据验证了所述方法的有效性。
[Abstract]:Spatial correlation of wind speed helps to improve the quality of its prediction, especially in the case of sudden changes in wind speed. The on-line matching model is applied to the ultra-short-term wind speed prediction based on spatial correlation. Through the time series analysis of historical data, the time period in which the wind speed of each wind farm is spatially correlated is identified. According to its time series and other conditional features, the wind velocity series in the observation window is divided into subsets of samples with different evolution patterns, and its special prediction model and parameters are optimized according to the training sample subsets of various forms in off-line environment. In online application, according to the evolution of wind velocity series in the current window and related conditional features, according to the matching model and parameters, The wind speed of the target wind farm is predicted according to the measured data of the reference wind farm. The effectiveness of the method is verified by the actual historical data.
【作者单位】： 东南大学电气工程学院;新能源与储能运行控制国家重点实验室(中国电力科学研究院);南瑞集团公司(国网电力科学研究院);智能电网保护和运行控制国家重点实验室;神华集团有限责任公司;国网甘肃省电力公司电力科学研究院;国网甘肃省电力公司风电技术中心;
【基金】：国家自然科学基金重点项目(61533010) NSFC-NRCT(中泰)合作研究项目(51561145011) 国家电网公司科技项目~~
【分类号】：TM614
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本文编号：1497871