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Power System State Estimation Based on Fusion of WAMS/SCADA Measurements: A Survey

机译：基于WAMS / SCADA测量结果融合的电力系统状态估计：一项调查

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摘要

In modern power system, there are two sets of measurement systems, SCADA system and WAMS system. Both of them have their own advantages, SCADA system has accumulated a wealth of operational experience in long-term operation, while WAMS system can provide more accurate and fast updated measurement data. This paper first gave a brief introduction to the SCADA and the WAMS systems, then summarized the difficulties and corresponding solutions of data fusion between them. Besides, the paper reviewed the state data mining method and three main algorithms of state estimation basing on the fusion of the two systems. It showed that by combining the measurement data features of the two systems, the accuracy of subsequent state data mining was greatly improved. Furthermore, the latest applications of deep learning for the SCADA/WAMS data fusion in power system were also presented in this paper. Finally, both the developments and trends of data fusion in SCADA and WAMS system were predicted.
机译：在现代电力系统中，有两套测量系统：SCADA系统和WAMS系统。两者都有各自的优势，SCADA系统在长期运行中积累了丰富的运行经验，而WAMS系统可以提供更准确，更快速的测量数据。本文首先简要介绍了SCADA和WAMS系统，然后总结了两者之间数据融合的困难和相应的解决方案。此外，本文还基于两个系统的融合，回顾了状态数据挖掘方法和状态估计的三种主要算法。结果表明，通过结合两个系统的测量数据特征，极大地提高了后续状态数据挖掘的准确性。此外，本文还介绍了深度学习在电力系统中的SCADA / WAMS数据融合的最新应用。最后，对SCADA和WAMS系统中数据融合的发展和趋势进行了预测。

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