Distribution Grid Phasor Estimation and μPMU Modeling

Elsayed, Ahmed Abd Elaziz; Mohamed, Magdi A.; Nayel, Mohamed

doi:10.1109/pesgre52268.2022.9715887

Cited by 1 publication

(4 citation statements)

References 22 publications

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“…In order to estimate the frequency and ROFC, the angle-based method is used. In this method, the change in the phasor angle is assumed to be a quadratic time function [15,16]. The phasor angle is stored for the last N estimated phasors and frequency defined by Eq.…”

Section: Frequency Estimationmentioning

confidence: 99%

“…E CT/VT , E AF , E ADC , E GPS and P are the complex gain error due to CT/VT scaling, analog filter error, ADC digitization error, GPS synchronization error and off-nominal complex gain P error, respectively. Each error has it is own nature and is required to be compensated, if possible, to ensure high estimation quality [15]. E ADC and E GPS depend on a random process and these errors are just minimized by the appropriate selection of the ADC and GPS.…”

Section: µPmu Error Estimation and Calibrationmentioning

confidence: 99%

“…The STU is defined as the maximum response time of the GPS module. The response time τ of the module is assumed to be a Gaussian Distribution function with mean and standard deviation equal to µ= 0.5STU and δ = STU/6, respectively [15]. In the proposed µPMU GPS module SIM808 module is used, which has synchronization time accuracy equals 10nsec , which gives an error in the angle of 0.00018 o while GPS magnitude is approximately one.…”

Section: Gps Errormentioning

confidence: 99%

“…3. Error estimation and compensation of each process inside µPMU were not implemented, which limits the previous design to reach the specification of the commercial µPMU [14,15].…”

Section: Introductionmentioning

confidence: 99%

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uPMU Hardware and Software Design Consideration and Implementation for Distribution Grid Applications

Elsayed¹,

Abdellah²,

Mohamed³

et al. 2022

Adv. sci. technol. eng. syst. j.

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Real-time monitoring system µPMU hardware and software design Error and phasor estimation Computational time minimization This article presents a roadmap for distribution grid µPMU hardware and software design consideration and implantation to ensure high performance within limited computational time of sampling frequency 512 samples/cycle. A proposed 12 channels, multi-voltage level µPMU hardware and rules of voltage and current transducer, analog filter, analog-to-digital converter, sampling rate definition, and PCB design and selection are presented. From the software view, software minimization procedures are implemented to reduce the estimation time of the proposed µPMU to 18 µsec under high sampling frequency operation. Additionally, error estimation and compensation are used to ensure robust performance, while the computational burden of the error compensation stage is reduced by Taylor series linearization. The proposed µPMU is designed to provide traditional phasor, frequency and harmonics measurements besides a point-on-wave under dynamic operation mode. The proposed device is tested under IEEE Std C37. 118.1 and 118.2 and showed accurate phasor estimation up to 0.03% for the magnitude and angle accuracy up to 0.0036 o , while the frequency is estimated with maximum variation of 0.032% under dynamic operation.

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Section: Frequency Estimationmentioning

confidence: 99%

Section: µPmu Error Estimation and Calibrationmentioning

confidence: 99%

Section: Gps Errormentioning

confidence: 99%

“…3. Error estimation and compensation of each process inside µPMU were not implemented, which limits the previous design to reach the specification of the commercial µPMU [14,15].…”

Section: Introductionmentioning

confidence: 99%

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