在物联网和光学成像技术下,分布网络设备的数字双胞胎模型的实时更新算法
Jian Shen1, Liang Hu2, Yang Yang1
1Shaoxing Power Supply Company of State Grid Zhejiang Electric Power Company Limited, Shaoxing, 312000, Zhejiang, China.
Scientific reports
|February 18, 2025
概括
本研究介绍了分布网络设备 (DNE) 数字双胞胎 (DT) 模型的改进实时更新算法. 新方法提高了准确性和效率,克服了智能设备管理传统方法的局限性.
科学领域:
- 电气工程 电气工程
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
背景情况:
- 分布网络设备 (DNE) 的数字化需要数字双胞胎 (DT) 模型的先进实时更新算法.
- 对于DNE的传统DT模型在实时准确性,稳定性和可扩展性方面面临挑战.
- 目前的方法很难有效地管理和更新现代DNE的复杂数据.
研究的目的:
- 为DNE DT模型开发和验证一种新的实时更新算法.
- 提高DNE管理的效率,准确性,稳定性和可扩展性.
- 解决现有的算法在处理DNE的数字化方面的局限性.
主要方法:
- 整合物联网 (IoT) 传感器和光学成像技术用于数据收集.
- 应用萨维茨基-戈莱过用于数据除.
- 使用递归最小方程方法来提取实时DT模型更新的密钥和状态参数.
主要成果:
- 拟议的算法实现了0.014秒的更新时间和93.2%的准确性,优于传统方法 (0.045秒,80.4%和0.056秒,82.7%).
- 与参数灵敏度分析和状态估计相比,显著提高了稳定性和可扩展性.
- 物联网和光学成像方法为DNE DT模型提供了卓越的实时性能和准确性.
结论:
- 为DNE DT模型开发的实时更新算法在速度,准确性,稳定性和可扩展性方面提供了卓越的性能.
- 这种物联网和光学成像技术的整合为智能变电站设备管理提供了可行的解决方案.
- 这些发现为加强DNE实时监测,预测和控制铺平了道路.
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