基于参数自适应摆门算法的风电坡道事件识别

Qi Weizhi, Che Jianfeng, Xiong Yuhan, Huo Xuesong, Hao Yuchen, Dai Qiangsheng
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引用次数: 0

摘要

风电坡道事件的准确识别对电网的安全稳定运行具有重要意义。为了提高实际风电坡道事件识别的准确性,提出了一种基于参数自适应摆门算法的方法。首先,对原始功率数据进行预处理,去除不合理的数据,降低噪声的影响。然后,提出了参数自适应摆门算法,在保持功率波动趋势的同时对数据进行压缩。最后,根据选取的定义和条件对风力坡道事件进行识别。案例分析表明,与摆门算法相比,本文提出的参数自适应摆门算法能够识别出更多真实的风斜坡事件,检出率提高了22.04%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wind Power Ramp Event Identification Based on Parameter Adaptive Swinging Door Algorithm
Accurate identification of wind power ramp event is of great significance for the safe and stable operation of power grid. In order to improve the accuracy of real wind power ramp event recognition, this paper proposed a method based on parameter adaptive swinging door algorithm. First, the original power data is preprocessing to remove the unreasonable data and reduce the impact of noise. Then, the parameter adaptive swinging door algorithm is proposed to compress data while retaining the power fluctuation trend. Finally, the wind power ramp event is identified according to the selected definition and condition. The case analysis shows that, compared with the swinging door algorithm, parameter adaptive swinging door algorithm proposed in this paper can identify more real wind ramp events, the increasing of detection rate can up to 22.04%.
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