| 基于风速高相关分区的风电场风速预报订正 |
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| 引用本文： | 石岚,徐丽娜,郝玉珠.基于风速高相关分区的风电场风速预报订正[J].应用气象学报,2016,27(4):506-512. |
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| 作者姓名： | 石岚 徐丽娜 郝玉珠 |
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| 作者单位： | 内蒙古气象服务中心, 呼和浩特 010051 |
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| 基金项目： | 资助项目： 中国气象局气象关键技术集成与应用项目（CMAGJ2015Z13），公益性行业（气象）科研专项（GYHY201206026） |
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| 摘 要： | 为了提高风电场风速预报和功率预测的精度和准确率，并考虑风机测风数据的不稳定因素，以多年服务的内蒙古中部某风力发电场A为研究区，在勘察风电场地形及风机布局后，按照季节、风向进行风机间风速时空相关性分析，划分出风机轮毂高度风速高相关为典型特征的风机网格分类片区，采用卡尔曼滤波方法，通过直接和间接两种订正方案，分别进行风机片区风速订正。结果表明:风速高相关风机片区的划分，对于提高风电场风速预报及功率预测精度和准确率具有一定作用，利用风电场区测风塔梯度观测风速，对风机片区进行间接订正，可有效改善数值模式预报风速，15个片区类型下相关系数由0.18~0.72提高至0.67~0.91，误差绝对值由1.6~2.9 m·s-1降低至1.0~1.5 m·s-1。
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| 关 键 词： | 风电场 风速相关 风机片区 风速订正 |
| 收稿时间： | 2015-12-02 |
| 修稿时间： | 3/2/2016 12:00:00 AM |
The Correction of Forecast Wind Speed in a Wind Farm Based on Partitioning of the High Correlation of Wind Speed |
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| Shi Lan,Xu Lina and Hao Yuzhu.The Correction of Forecast Wind Speed in a Wind Farm Based on Partitioning of the High Correlation of Wind Speed[J].Quarterly Journal of Applied Meteorology,2016,27(4):506-512. |
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| Authors: | Shi Lan Xu Lina and Hao Yuzhu |
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| Affiliation: | Inner Mongolia Service Center of Meteorology, Hohhot 010051 |
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| Abstract: | In order to improve precision and accuracy of wind speed forecast and wind power prediction, and taking unstable factors of observations on the wind turbines into account, a refined and partitioned correction model is established for improving the quality of wind speed forecast on turbine hub height. The wind farm A, which is located in the middle of Inner Mongolia of China, is selected as the target area. Fine analysis on gradient observation, the terrain and the layout of the wind turbines is carried out, and the hourly quality-controlled wind data on the wind tower and the turbine hub height are comprehensive compared, considering the spatial-temporal correlation, deviation of wind tower and turbine wind speed, seasonal influences and wind directions (NW, SW, NE, SE). Wind turbine groups are partitioned by wind speed subsequently in wind farm A. Characteristics of wind speed of wind tower and groups that are affected by turbulence, wake flow and wake superposition are studied. Using the method of Kalman filter, through direct (from numerical model to turbine groups directly) and indirect (from numerical model to the wind tower firstly, and then to the turbine groups) correction schemes, wind speed correction is done, respectively.Results show that the division of wind turbine groups in every wind speed is high correlative. The indirect correction of turbine groups using the gradient observation of the wind tower can correct wind speed forecast more effectively than model forecast and direct correction. Correlation (R) and the absolute value of error (E) between corrected wind speed of indirect correction and observed wind speed are improved by different degrees in each wind turbine group. R increases from 0.18-0.72 to 0.67-0.91, and E is reduced from 1.6-2.9 m·s-1 to 1.0-1.5 m·s-1 after indirect correction, compared to R increasing to 0.39-0.87 and E decreasing to 1.2-2.1 m·s-1 after direct correction. In addition, the indirect correction scheme plays a very good role in controlling the E of the low velocity section ( < 3 m·s-1) and the high speed section (>9 m·s-1). The indirect correction scheme performs better when the difference between forecast wind speed and observed wind speed are relatively larger. Therefore, this method has is a good reference for improving prediction precision and accuracy, and it should be tested and spread to more wind farms in the service. |
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| Keywords: | wind farm wind speed correlation wind turbine groups wind speed correction |
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