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Research on wind power ramp events prediction based on strongly convective weather classification

机译：基于强对流天气分类的风电匝道事件预测研究

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摘要

In this study a forecasting model for wind power ramps based on strongly convective weather classification is presented. First, the dynamics and thermodynamic behaviours of strongly convective weather are characterised by the predictors in the selected region. Then the support vector domain description for ramps scenario classification is introduced to establish an initialised extremum model, and the parameter templates method is used to identify the ramps weather in strongly convective weather library. Meanwhile, the original wind speed data is modified to obtain more accurate wind speed, and a new wind power ramps definition is proposed based on the ramp character itself and its impact on the power grid. Thus the catastrophe detection method (Bernaola Galvan algorithm) used for strongly convective weather forecasting. Finally, the wind power ramps forecasting method based on the discrimination of convective weather is developed. Comparing with the existing wind power ramps forecasting algorithms, the proposed prediction method here gets into meteorologic essence of triggering great fluctuation of wind speed.
机译：在这项研究中，提出了一种基于强对流天气分类的风电斜坡预测模型。首先，强对流天气的动力学和热力学行为由所选区域中的预测因子来表征。然后引入用于坡道场景分类的支持向量域描述，建立初始化的极值模型，并采用参数模板方法识别强对流天气库中的坡道天气。同时，对原始风速数据进行修改以获得更准确的风速，并根据坡度特征及其对电网的影响，提出了新的风电坡度定义。因此，将突变检测方法（Bernaola Galvan算法）用于强对流天气预报。最后，开发了基于对流天气判别的风电斜率预测方法。与现有的风电斜率预测算法相比，本文提出的预测方法进入了引发风速大幅度波动的气象本质。

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