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Abstract:
The challenge of unobservability arising from insufficient measurement equipment has emerged as a critical impediment to achieving precise state estimation in distribution networks. Integrating traditional supervisory control and data acquisition (SCADA) data with advanced metering infrastructure (AMI) data can effectively enhance the redundancy of network measurement information, resulting in a more extensive and accurate state estimation results. However, the low resolution of AMI data is incapable of supporting the high-resolution real-time state estimation. To address this issue, a dynamic state estimation method for distribution networks based on pseudo-measurement modeling is proposed. Firstly, the mapping model between SCADA data and AMI data is established based on Gated Recurrent Unit (GRU), enabling the generation of real-time high-resolution pseudo-measurement data for AMI. Secondly, leveraging the SCADA measurement timestamps, a multi-source measurement dataset incorporating both the pseudo-measurement data and real-time measurement data is constructed. And then the dynamic state estimation of the distribution networks can be achieved based on the dataset. Finally, simulation based on IEEE 33-bus test network verifies the effectiveness of the proposed method.
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Source :
2023 2ND ASIAN CONFERENCE ON FRONTIERS OF POWER AND ENERGY, ACFPE
Year: 2023
Page: 134-139
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ESI Highly Cited Papers on the List: 0 Unfold All
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30 Days PV: 0
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