Journal of Modern Power Systems and Clean Energy

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Home > Archive>Volume 11, Issue 5, 2023 >1540-1552. DOI:10.35833/MPCE.2022.000200
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Robust State Estimation of Active Distribution Networks with Multi-source Measurements
Author:
Affiliation:

1. Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
2. Digital Grid Research Institute of China Southern Power Grid, Guangzhou 510670, China
3. Institute of Energy, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK

Fund Project:

This work was supported by the National Key R&D Program of China (No. 2020YFB0906000 and 2020YFB0906001).

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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.

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History
  • Received:April 05,2022
  • Revised:July 17,2022
  • Online: September 20,2023

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