一种基于tsDatawig的功率负载时间序列数据的新归算方法
Hui Wang1,2, Fafa Zhang1, Yujing Cai1
1School of Artificial Intelligence, Anhui University, Jiulong Road, Hefei, 230601, Anhui, China.
Scientific reports
|July 2, 2025
概括
本研究引入了一种新的时间编码归算方法,使用tsDataWig来解决传感器网络中缺少的功率负载数据. 提出的方法有效地预测缺失的值,提高功率负载预测的准确性.
科学领域:
- 电气工程 电气工程
- 数据科学数据科学数据科学
背景情况:
- 准确的功率负载预测对于优化电网运行和单元调度至关重要.
- 来自传感器网络的实时负载数据对于预测模型至关重要.
- 传感器网络中因故障或干扰而造成的数据缺口是一个重大挑战.
研究的目的:
- 提出和评估一种新的数据归算方法,以解决缺少的功率负载数据.
- 提高功率负载预测模型的准确性和可靠性.
主要方法:
- 使用数据归算方法分析了历史功率负载数据.
- 基于tsDataWig的时间编码方法被开发用于数据预处理和编码.
- 数据集是故意掩盖使用三个不同的缺失数据机制.
- 使用tsDataWig方法构建了一个功率负载数据归算框架.
主要成果:
- 提出的基于tsDataWig的归算方法比现有方法具有显著的优势.
- 实验结果显示,与其他方法相比,预测误差始终较低.
- 该方法有效地证实了其在预测缺失功率负载值方面的能力.
结论:
- 开发的时间编码归算方法有效地解决了传感器网络中数据缺失漏洞的问题.
- 这种方法提高了功率负载数据的可靠性,从而改善了电网运行和预测.
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