Topology Identification Method of Distribution Network Based on Smart Meter Measurements

Zhang, Mingze; Luan, Wenpeng; Guo, Shen; Wang, Peng

doi:10.1109/ciced.2018.8592228

Cited by 24 publications

(13 citation statements)

References 9 publications

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“…The dualchannel integral filter circuit in the flexible transformer shall extract and separate the signal coupling of 50 Hz and high-frequency. The flexible transformer has the following characteristics [9] .…”

Section: Address Codingmentioning

confidence: 99%

A Physical Topology Identification Method for Low-voltage Distribution Areas Meter Box

Wang¹,

Mao²,

Luo³

et al. 2023

J. Phys.: Conf. Ser.

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This paper put forward a method on the premise of not changing the hardware circuit of the HPLC communication unit of the online electrical meter. In the HPLC communication unit of the electrical meter, the electrical meter address is modulated to the electric-power line through a high-speed carrier signal by the method of on-off keying. In the intelligent molded case circuit breaker of the meter box, after the new-type instrument transformer is used to extract the signal, the optimization algorithm is adopted to extract the electrical meter address to achieve physical topology identification of the meter box, forming a physical topographic map of low-voltage distribution area at the meter box level, which has the characteristics of low cost and high identification rate. This method is particularly suitable for the situation where HPLC communication units have been used in large quantities. Based on the current meter box operating method, it can effectively achieve the physical topology identification for the low-voltage distribution area, improve the physical topology identification rate for the meter box and reduce the identification cost.

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Section: Address Codingmentioning

confidence: 99%

A Physical Topology Identification Method for Low-voltage Distribution Areas Meter Box

Wang¹,

Mao²,

Luo³

et al. 2023

J. Phys.: Conf. Ser.

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show abstract

“…However, this method can be misjudged when user voltages within different stations are in close proximity to each other. The literature [4] is based on AMI measurement information for household variable identification, which is more comprehensive compared to just voltage information analysis. A topology identification method based on discrete Fréchet distances and edited nearest neighbour method is proposed in the literature [5].…”

Section: Introductionmentioning

confidence: 99%

A Novel Topology Identification Algorithm Fusing Multi-Source Measurement Data in Distribution Network

Zhang

Liu

Huang

et al. 2023

J. Phys.: Conf. Ser.

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With the development of new power systems, large amounts of decentralised clean energy and flexible loads will be connected to the smart grid, making the topology of the distribution network even more complex. At the same time, the demand for efficient interaction of “source-network-load” also makes the distribution network topology change with time, which makes it more difficult to identify the distribution network topology. However, topology identification is the basic data for power system regulation and safe optimal operation. Considering the above problems and requirements, this paper investigates and proposes a novel method to identify the topology of a distribution network based on the collaboration of data from multiple measurement devices. Firstly, a method based on multi-source data time synchronization method of μPMU measurement data is proposed, and generate additional data based on linear extrapolation to expand the available data set. Then, a method of topology optimization model identification based on least square method is proposed. Finally, the proposed algorithm is simulated in an example of the IEEE 33 bus feeder system standard. The results show that the scheme is effective in identifying the topology of the distribution network and improves the accuracy compared to traditional methods.

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“…Although this method has advantages in low cost and long transmission distance of the modulated signal, power line may distortion in zero-crossing point with harmonic interference, so its reliability is not high [7]. In Refs [8][9][10], a correlation analysis method of user electricity meter data are proposed to help phase identification. References [11] and [12] combine machine learning and fuzzy algorithm with electricity meter data, and the recognition success rate is high.…”

Section: Introductionmentioning

confidence: 99%

Phase Identification of Distribution Network Based on Phasor Angle Measurement

Liu

Cheng

et al. 2022

IEEJ Transactions Elec Engng

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Because of the crosstalk of neutral line signals in adjacent distribution transformers, the phase attribution relationship between users and transformer is not clear, which brings difficulties to the collection of users' electricity consumption information, file management, and power systems business development. Accordingly, this paper proposes a phase identification method for distribution network users based on dynamic phasor measurement, which can effectively identify all phase meter devices under the same station area. Firstly, considering that the signal on the power line contains complex frequency components and interference, the time‐varying phasor is approximated by the Taylor series. Secondly, by combining the discrete Fourier transform results of two adjacent data windows and calling the offline calculation matrix, accurate phasor measurements can be obtained. Phase shift processing is to obtain the phase angle of the bus line on the low‐voltage side of the transformer and the user at the same reporting time. In addition, the phase angle distortion caused by the impedance of the transmission line under different currents is also considered, so we make phase angle compensation to decrease the influence of the impedance of the line on the voltage phase angle. Simulation results and field experiments show that the proposed method can achieve a recognition success rate of 100% under frequency deviation conditions. Under the dynamic modulation and harmonic interference conditions, the recognition success rate could achieve 94.83% and 96.55%, respectively, it is much higher than that of the voltage correlation analysis method. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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Topology Identification Method of Distribution Network Based on Smart Meter Measurements

Cited by 24 publications

References 9 publications

A Physical Topology Identification Method for Low-voltage Distribution Areas Meter Box

A Physical Topology Identification Method for Low-voltage Distribution Areas Meter Box

A Novel Topology Identification Algorithm Fusing Multi-Source Measurement Data in Distribution Network

Phase Identification of Distribution Network Based on Phasor Angle Measurement

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