Srinivas, Vedantham Lakshmi and Wu, Jianzhong ORCID: https://orcid.org/0000-0001-7928-3602 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 |
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Abstract
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 |
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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 |
URI: | https://orca.cardiff.ac.uk/id/eprint/150421 |
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