Robust state estimation of active distribution networks with multi-source measurements

Liu, Zhelin, Li, Peng, Wang, Chengshan, Yu, Hao, Ji, Haoran, Xi, Wei and Wu, Jianzhong ORCID: https://orcid.org/0000-0001-7928-3602 2023. Robust state estimation of active distribution networks with multi-source measurements. Journal of Modern Power Systems and Clean Energy 11 (5) , pp. 1540-1552. 10.35833/MPCE.2022.000200

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Abstract

The volatile and intermittent nature of distributed generators (DGs) in active distribution networks (ADNs) increases the uncertainty of operating states. The introduction of distribution phasor measurement units (D-PMUs) enhances the monitoring level. The trade-offs of computational performance and robustness of state estimation in monitoring the network states are of great significance for ADNs with D-PMUs and DGs. This paper proposes a second-order cone programming (SOCP) based robust state estimation (RSE) method considering multi-source measurements. Firstly, a linearized state estimation model related to the SOCP state variables is formulated. The phase angle measurements of D-PMUs are converted to equivalent power measurements. Then, a revised SOCP-based RSE method with the weighted least absolute value estimator is proposed to enhance the convergence and bad data identification. Multi-time slots of D-PMU measurements are utilized to improve the estimation accuracy of RSE. Finally, the effectiveness of the proposed method is illustrated in the modified IEEE 33-node and IEEE 123-node systems.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	2196-5625
Date of Acceptance:	30 August 2022
Last Modified:	01 Nov 2023 10:15
URI:	https://orca.cardiff.ac.uk/id/eprint/163397

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