This paper presents the assessment of an enhanced line parameter estimation technique for modern distribution networks. The estimation method takes advantage of the use of Phasor Measurement Units or, more in general of synchronized phasor measurements. A comprehensive modeling of the uncertainty of synchronized data permits performing an accurate estimation. The validity of the estimation technique has been tested on a portion of the digital twin of the Forschungszentrum Jülich (FZJ) campus, a self-managed distribution network with more than 100 nodes. Realistic measurement assumptions have been considered by taking into account the accuracy of a measurement chain (instrument transformer and measurement device) for distribution networks. Furthermore, the presence of distributed generation has been also taken into account. The results will show that the parameter estimation in these challenging conditions is successful, and the technique can be applied for the analysis of real distribution networks.
Performance Assessment of Synchronized Phasor Measurement-Based Parameter Estimation for Distribution Networks
Sitzia, Carlo;Pegoraro, Paolo Attilio;Sulis, Sara
2022-01-01
Abstract
This paper presents the assessment of an enhanced line parameter estimation technique for modern distribution networks. The estimation method takes advantage of the use of Phasor Measurement Units or, more in general of synchronized phasor measurements. A comprehensive modeling of the uncertainty of synchronized data permits performing an accurate estimation. The validity of the estimation technique has been tested on a portion of the digital twin of the Forschungszentrum Jülich (FZJ) campus, a self-managed distribution network with more than 100 nodes. Realistic measurement assumptions have been considered by taking into account the accuracy of a measurement chain (instrument transformer and measurement device) for distribution networks. Furthermore, the presence of distributed generation has been also taken into account. The results will show that the parameter estimation in these challenging conditions is successful, and the technique can be applied for the analysis of real distribution networks.File | Dimensione | Formato | |
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