Open Access

ARTICLE

A Novel Three-Phase Dynamic State Estimation Method for Low-Voltage Distribution Network Based on Data Fusion Technology

Zhaofeng Guo¹, Fei Yu², Bingyao Hu¹, Chen Yang¹, Ronghao Yang¹, Shiao Wang³, Hongbo Zou^3,*
1 Information and Communication Branch, State Grid Hubei Electric Power Co., Ltd., Wuhan, China
2 State Grid Hubei Electric Power Co., Ltd., Wuhan, China
3 School of Electricity and New Energy, Three Gorges University, Yichang, China
* Corresponding Author: Hongbo Zou. Email:
(This article belongs to the Special Issue: AI-Enabled Resilient Distribution Networks and Active Distribution Systems)

Energy Engineering https://doi.org/10.32604/ee.2026.087120

Received 10 June 2026; Accepted 29 July 2026; Published online 27 August 2026

Abstract

To bridge the last mile of situational awareness in the end-section networks of smart distribution grids and achieve precise three-phase dynamic state estimation (DSE) for low-voltage distribution network (LDN), by taking into account both phasor measurement units (PMU) in LDN and smart meters (SM) within the advanced metering infrastructure, a novel three-phase dynamic state estimation method for LDN based on data fusion (DF) technology is proposed in this paper. Firstly, this method constructs a three-phase four-wire network model for LDN that incorporates the impact of the neutral wire, as well as a state-space model capable of describing the dynamic characteristics of loads and distributed generation. Subsequently, a multi-source heterogeneous DF framework is designed. During the filtering process for each snapshot, the method establishes parallel three-phase DSE models for LDN by combining predicted values with PMU measurements and by combining predicted values with SM measurements, respectively. Based on the results of parallel filtering, DF technology is employed to integrate the states and obtain the final estimated values for that time section. Finally, simulations of the proposed LDN three-phase DSE method are conducted by using a modified IEEE-13 bus system, the numerical results indicate that the proposed method consistently and uniformly exhibits sustained improvements in state estimation accuracy and computational efficiency across various tested scenarios.

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Keywords

Data fusion technology; low voltage distribution network; three-phase dynamic state estimation; smart distribution network

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