Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Topology and parameter identification of distribution network using smart meter and µPMU measurements

Srinivas, Vedantham Lakshmi and Wu, Jianzhong ORCID: 2022. Topology and parameter identification of distribution network using smart meter and µPMU measurements. IEEE Transactions on Instrumentation and Measurement 71 , pp. 1-14. 10.1109/TIM.2022.3175043

[thumbnail of Topology_and_Parameter_Identification_of_Distribution_Network_Using_Smart_Meter_and_PMU_Measurements.pdf] PDF - Published Version
Available under License Creative Commons Attribution.

Download (5MB)


Incomplete and inaccurate information of network topology and line parameters affects state monitoring, analysis, and control of active distribution networks. To solve this issue, this article proposes a method for identifying distribution network topology and line parameters using the measurements obtained from smart meters (SMs) and microphasor measurement units ( μ PMUs) installed at various locations in a distribution network. A data-driven approach was developed, which uses a probabilistic method (unscented Kalman filter (UKF) based) and a deterministic method (Newton Raphson (NR) based) iteratively for accurate identification of network topology and parameters. The impact of the measurement noise with SMs and μ PMUs is analyzed, and the acceptable noise levels are quantified. The impact of the identification algorithm on the network state estimation is examined. Moreover, optimal installation locations of the μ PMU equipment are identified based on the estimation accuracy of the algorithm. The method is validated on benchmarked IEEE 33-bus and IEEE 123-bus test systems, while the impact of the renewable power injections at the different network nodes is studied as well. The qualitative and quantitative analysis is performed over the state-of-the-art methods, to highlight the effectiveness of the proposed methodology.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Institute of Electrical and Electronics Engineers
ISSN: 0018-9456
Date of First Compliant Deposit: 15 June 2022
Date of Acceptance: 23 April 2022
Last Modified: 14 May 2023 09:52

Citation Data

Cited 1 time in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics