The Design of a Low Cost Phasor Measurement Unit

Femine, Antonio Delle; Gallo, Daniele; Landi, C.; Luiso, Mario

doi:10.3390/en12142648

Cited by 14 publications

(7 citation statements)

References 36 publications

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“…This solution, while cheaper than commercial solutions, aimed to achieve high performance and for this reason was still based on relatively expensive hardware. Cheaper PMUs based on single-board computers (SBC) were proposed in [ 10 ], using a Raspberry Pi, in [ 11 ], using a Beagle Bone Black, and in [ 12 ], adopting an ARM microcontroller. Recently, an improved PMU design based on Raspberry Pi has been described in [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

SMU Open-Source Platform for Synchronized Measurements

Carducci

Pau

Cazal

et al. 2022

Sensors

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The ramping trend of cheap and performant single board computers (SBC) is growingly offering unprecedented opportunities in various domains, taking advantage of the widespread support and flexibility offered by an operating system (OS) environment. Unfortunately, data acquisition systems implemented in an OS environment are traditionally considered not to be suitable for reliable industrial applications. Such a position is supported by the lack of hardware interrupt handling and deterministic control of timed operations. In this study, the authors fill this gap by proposing an innovative and versatile SBC-based open-source platform for CPU-independent data acquisition. The synchronized measurement unit (SMU) is a high-accuracy device able to perform multichannel simultaneous sampling up to 200 kS/s with sub-microsecond synchronization precision to a GPS time reference. It exhibits very low offset and gain errors, with a minimum bandwidth beyond 20 kHz, SNR levels above 90 dB and THD as low as −110 dB. These features make the SMU particularly attractive for the power system domain, where synchronized measurements are increasingly required for the geographically distributed monitoring of grid operating conditions and power quality phenomena. We present the characterization of the SMU in terms of measurement and time synchronization accuracy, proving that this device, while low-cost, guarantees performance compliant with the requirements for synchrophasor-based applications in power systems.

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Section: Introductionmentioning

confidence: 99%

SMU Open-Source Platform for Synchronized Measurements

Carducci

Pau

Cazal

et al. 2022

Sensors

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“…In the literature, many publications may be found regarding the estimation methods of the synchrophasor magnitude, angle and frequency, as well as calculating the synchrophasor errors defined in standards [2][3][4]. Fourier transform (FT) [5] and its variations [6][7][8][9][10][11][12][13][14] are the most popular methods used to measure the signal magnitude and angle, since they are efficient and mostly reliable. In turn, the quadrature filter method is based on the multiplication of the input signal by two sinusoidal orthogonal functions with the nominal frequency [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Application of an Artificial Neural Network for Measurements of Synchrophasor Indicators in the Power System

2021

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Dynamic phenomena in electric power systems require fast and accurate algorithms for processing signals. The processing results include synchrophasor parameters, e.g., varying amplitude, phase or frequency of sinusoidal voltage or current signals. This paper presents a novel estimation method of synchrophasor parameters that comply with the requirements of IEEE/IEC standards. The authors analyzed an algorithm for measuring the phasor magnitude by means of a selected artificial neural network (ANN), an algorithm for estimating the phasor phase and frequency that makes use of the zero-crossing method. The original components of the presented approach are: the method of the synchrophasor magnitude estimation by means of a suitably trained and applied radial basic function (RBF); the idea of using two algorithms operating simultaneously to estimate the synchrophasor magnitude, phase and frequency that apply identical calculation methods are different in that the first one filters the input signal using the FIR filter and the second one operates without any filter; and the algorithm calculating corrections of the phase shift between the input and output signal and the algorithm calculating corrections of the magnitude estimation. The error results obtained from the applied algorithms were compared with those of the quadrature filter method and the ones presented in literature, as well as with the permissible values of the errors. In all cases, these results were lower than the permissible values and at least equal to the values found in the literature.

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“…• Automation and control systems [9], that need an accurate common notion of time as well as a reliable shared communication medium for timely data exchange, for instance to synchronize multi axis drive systems and subsystems with cyclic operation; • Measurement and automatic test systems [10], which usually take advantage of accurate time stamping of logged data, for example to correlate acquired values in decentralized locations; • Power generation, transmission and distribution systems [11,12], requiring a precise time synchronization of all the critical points within the power grid to accurately measure the delivered/consumed power and to predict critical load situations.…”

Section: Introductionmentioning

confidence: 99%

Trusted GNSS-Based Time Synchronization for Industry 4.0 Applications

Margaria

Vesco

2021

Applied Sciences

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The protection of satellite-derived timing information is becoming a fundamental requirement in Industry 4.0 applications, as well as in a growing number of critical infrastructures. All the industrial systems where several nodes or devices communicate and/or coordinate their functionalities by means of a communication network need accurate, reliable and trusted time synchronization. For instance, the correct operation of automation and control systems, measurement and automatic test systems, power generation, transmission, and distribution typically require a sub-microsecond time accuracy. This paper analyses the main attack vectors and stresses the need for software integrity control at network nodes of Industry 4.0 applications to complement existing security solutions that focus on Global Navigation Satellite System (GNSS) radio-frequency spectrum and Precision Time Protocol (PTP), also known as IEEE-1588. A real implementation of a Software Integrity Architecture in accordance with Trusted Computing principles concludes the work, together with the presentation of promising results obtained with a flexible and reconfigurable testbed for hands-on activities.

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The Design of a Low Cost Phasor Measurement Unit

Cited by 14 publications

References 36 publications

SMU Open-Source Platform for Synchronized Measurements

SMU Open-Source Platform for Synchronized Measurements

Application of an Artificial Neural Network for Measurements of Synchrophasor Indicators in the Power System

Trusted GNSS-Based Time Synchronization for Industry 4.0 Applications

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