Smart Grid State Estimation with PMUs Time Synchronization Errors

Marco Todescato, Ruggero Carli, Luca Schenato and Grazia Barchi
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Marco Todescato: Bosch Center for Artificial Intelligence, 71272 Renningen, Germany
Ruggero Carli: Department of Information Engineering, University of Padova, via Gradenigo 6/b, 35131 Padova, Italy
Luca Schenato: Department of Information Engineering, University of Padova, via Gradenigo 6/b, 35131 Padova, Italy
Grazia Barchi: Institute for Renewable Energy, Eurac Research, viale Druso 1, 39100 Bolzano, Italy

Energies, 2020, vol. 13, issue 19, 1-20

Abstract: State Estimation (SE) is one of the essential tasks to monitor and control the smart power grid. This paper presents a method to estimate the state variables combining the measurement of power demand at each bus with the data collected from a limited number of Phasor Measurement Units (PMUs). Although PMU data are usually assumed to be perfectly synchronized with the Coordinated Universal Time (UTC), this work explicitly considers the presence of time-synchronization errors due, for instance, to the actual performance of GPS receivers and the limited stability of the internal oscillator. The proposed algorithm is a recursive Kalman filter which not only estimates the state variables of the power system, but also the frequency deviations causing clock offsets which eventually affect the timestamps of the measures returned by different PMUs. The proposed solution was tested and compared with alternative approaches using both synthetic data applied to the IEEE 123 bus distribution feeder and real-field data collected from a small-size medium-voltage (MV) distribution system located inside the EPFL campus in Lausanne. Results show the validity of the proposed method in terms of state estimation accuracy. In particular, when some synchronization errors are present, the proposed algorithm can estimate and compensate for them.

Keywords: state estimation; phasor measurement units; Kalman filter; time synchronization; smart grids (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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