| Autor: |
Zhelin Liu, Peng Li, Chengshan Wang, Hao Yu, Haoran Ji, Wei Xi, Jianzhong Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Journal of Modern Power Systems and Clean Energy, Vol 11, Iss 5, Pp 1540-1552 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2196-5420 |
| DOI: |
10.35833/MPCE.2022.000200 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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