2016
DOI: 10.1016/j.ifacol.2016.10.764
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Hybrid State Estimation Model Based on PMU and SCADA Measurements

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Cited by 8 publications
(2 citation statements)
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“…μPMU is not economical for distribution networks with large node size to achieve system observability just by installing the μPMU (Kandenkavil and Bhattacharya, 2018), a method of combining traditional measurement data with μPMU data to build a hybrid measurement state estimation method is provided. The hybrid weighted least squares state estimation algorithm based on PMU and SCADA is proposed in the study by Skok et al (2016), Silva et al (2017), and Santos and Orillaza (2018) for the three-phase unbalanced distribution network system, which not only ensures the global observability of the system, but also satisfies the economy and improves the accuracy of state estimation. A fast three-phase state estimation method based on hybrid measurements is proposed in He et al (2021).…”
Section: Introductionmentioning
confidence: 99%
“…μPMU is not economical for distribution networks with large node size to achieve system observability just by installing the μPMU (Kandenkavil and Bhattacharya, 2018), a method of combining traditional measurement data with μPMU data to build a hybrid measurement state estimation method is provided. The hybrid weighted least squares state estimation algorithm based on PMU and SCADA is proposed in the study by Skok et al (2016), Silva et al (2017), and Santos and Orillaza (2018) for the three-phase unbalanced distribution network system, which not only ensures the global observability of the system, but also satisfies the economy and improves the accuracy of state estimation. A fast three-phase state estimation method based on hybrid measurements is proposed in He et al (2021).…”
Section: Introductionmentioning
confidence: 99%
“…3-Identification of the line parameters by using the PMUs at the both ends of transmission lines, to get the parameters dynamically [91].…”
Section: Precise Measurements and The Benefits For Scadamentioning
confidence: 99%