风力发电中的电力坡道分类的新方法
M Saber Eltohamy1,2, M Said Abdel Moteleb3, Hossam E A Talaat4
1Department of Power Electronics and Energy Conversion, Electronics Research Institute, Cairo, Egypt. mohammed_saber@eri.sci.eg.
Scientific reports
|December 5, 2023
概括
新的方法更准确地对来自可再生能源的动力坡道事件进行分类. 尽管风力发电量翻了一番,但道行为仍然保持一致,帮助电网运营商平衡能源供应.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 电力系统分析 分析 分析
背景情况:
- 通过快速的电力变化特征的道事件,随着可再生能源的整合而增加.
- 准确预测和分类这些坡道对于电网稳定性至关重要,但仍然具有挑战性.
- 现有的二进制分类方法过于简化了坡道事件的可变性.
研究的目的:
- 开发和评价用于分类动力坡道事件的新方法.
- 提高对坡道事件特征和频率的理解.
- 为电网运营商提供更好的工具来管理可再生能源的变化.
主要方法:
- 引入了基于标准偏差分数和历史最大功率值的两个新分类方法.
- 将这些方法应用于2015年至2019年的比利时风电场总产量数据.
- 确定了每个新定义的道类别的相对频率.
主要成果:
- 开发的分类方法提供了对道事件的更细致的理解.
- 对比利时风电场数据 (2015-2019) 的分析显示,多年来,风电场的增速一直保持一致.
- 尽管风电装机容量翻了一番,但坡行为基本保持不变.
结论:
- 新的分类技术为动力坡道事件分析提供了更高的准确性.
- 一致的坡道行为表明风能变化的可预测模式.
- 调查结果支持改进的电网运营策略,以整合高水平的可再生能源发电.
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