基于波波变换和BIGRU-LSTM的高比例新能源分配网络线路损失频率分割预测
Xiangming Wu1, Nan Song1, Jifeng Liang2
1State Grid Hebei Electric Power Co., Ltd., Shijiazhuang City, Hebei Province, China.
PloS one
|August 19, 2024
概括
本研究引入了一种新的频率分割预测方法,用于电力线路损失,利用波形变换和BIGRU-LSTM网络. 这种方法通过分析不同频段的线路损失数据来提高预测的准确性.
科学领域:
- 电气工程 电气工程
- 数据科学数据科学数据科学
- 预测分析是一种预测分析.
背景情况:
- 整合新能源使配电网络运行复杂化,导致复杂的线路损失机制.
- 线路损失数据表现出非线性,波动和多尺度的特征,这给预测带来了挑战.
研究的目的:
- 为线路损失频率划分预测提出一种新方法.
- 通过解决其复杂特征,提高电力线路损失预测的准确性.
主要方法:
- 利用灰色关系分析和改进的NARMA相关性分析来提取影响因素.
- 应用波波变换将历史线路损失数据分解为不同的频段.
- 开发了一种BIGRU-LSTM (双向门式反复单元长期短期记忆网络) 用于高频和低频组件的概率预测.
主要成果:
- 提出的方法准确地匹配了不同线路损失组件和影响因素之间的映射关系.
- 数字模拟验证了频率划分预测方法的有效性和适用性.
- 实现了对电力线路损失的预测准确度的提高.
结论:
- 频率划分预测线路损失数据通过单独分析组件来提高准确性.
- 与波形变换集成的BIGRU-LSTM模型对于复杂的线路损失预测是有效的.
- 这种方法提供了一个强大的解决方案,用于管理现代发电网中的线路损失.
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