Effective monitoring of power system with phasor measurement unit and effective data storage system

Ponnala, Ravi; Chakravarthy, M.; Lalitha, S. V. N. L.

doi:10.11591/eei.v11i5.4085

Cited by 3 publications

(3 citation statements)

References 21 publications

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“…It is also advisable to subsequently use Markov models of this system, as well as carry out mathematical modeling of the activity of object components in real time [22]. In this case, broad prospects for effective monitoring of the water supply system using the methods described in [23] open up. For this purpose, approaches to automation of monitoring described in [24] may be useful.…”

Section: The Proposed Solution/methodsmentioning

confidence: 99%

Investigation of linear models for control of water flow and temperature in a water supply system

Asset,

Mansurova,

Zhmud

et al. 2024

IJEECS

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In some cases, the object model is a set of parallel models of the same general appearance, but with different parameters. The most common model is a model in the form of a serial connection of a first- or second-order filter and a delay link. An example is the water supply system of a large residential building or a group of houses. From the most general considerations, we can expect that such an object can be approximately described by a simpler model, replacing the sum of identical-looking models with different parameters with a single model of this type with averaged parameters, however, finding many parameters simply in the form of an average is, apparently, an unreasonable approach. It seems more reasonable to find the parameters by the approximating model by numerical optimization, in which the integral from the module or from the square of the deviation of the output signal of such a model from the output signal of the exact model is minimized when the test signal is applied. For linear models, the most reasonable test signal is a single step effect. This article tests this hypothesis and provides the results of this test.

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Section: The Proposed Solution/methodsmentioning

confidence: 99%

Investigation of linear models for control of water flow and temperature in a water supply system

Asset,

Mansurova,

Zhmud

et al. 2024

IJEECS

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“…In modern days, with the advancement of power electronics, the usage of power electronic converters is increasing rapidly. However, due to the non-linearity/switching action, harmonics are injected into the current waveforms [11][12]. Due to this, the fundamental current waveforms get disturbed and the total current waveform is distorted.…”

Section: Phasor Calculation Techniquesmentioning

confidence: 99%

Development and Implementation of Synchronized Phasor Measurements for Dynamic State Power System Monitoring and Fault Identification

Ponnala,

Chakravarthy,

Babu

et al. 2024

Preprint

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In real time the magnitude and phase angle of the voltage and current signals vary continuously. The measurement of magnitude and phase angles of these signals are very important for the visualization of real-time power systems pictorially and knowing dynamic power flow studies. This work presents the measurement of the voltage and current signal's magnitude and phase angles with time synchronization. The magnitude and phase angle are represented with a single quantity phasor. For the measurement of phasor values two different techniques are used, they are Recursive Discrete Fourier Transform (RDFT), and Non-Recursive Discrete Fourier Transform (NRDFT). With the RDFT the phasor (magnitude and phase angle) values are constant with time variation, with fixed load and constant supply. By varying the load or source the magnitude of the phasor is changed and the phase angle is constant. The values obtained from these results are used for the dynamic power flow calculation of the power system. With the NRDFT the phasor magnitude is constant the phase angle values are varying (rotating) with a speed of (ωt) and with a step of (1/N). The values obtained with this method are used for real-time power system visualization. The values obtained from the RDFT and NRDFT are time-stamped with GPS time. With GPS time stamping, the measurements are time synchronized, and real-time visualization of the power system is obtained.

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“…Instead of impedance-based fault calculation, signal analysis methods are better for fault detection and identification [12]. Different signal analysis methods are presented [13] to monitor and detect the faults in the dynamic state. The conventionally available PMUs use the Discrete Fourier Transform (DFT), and Taylor approximation [14] is used for the Phasor calculation.…”

Section: ░ 1 Introductionmentioning

confidence: 99%

Novel PMU Model for Dynamic State Disturbance Analysis with Effective Data Handling System

Ponnala¹,

Chakravarthy²,

Lalitha

2022

IJEER

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In this paper a hybrid DFT phasor calculation method is presented. This method is used to calculate the fundamental component phasor value of the harmonic signal without any physical filter. With this method the computational time for each phasor value calculation is reduced and the calculated phasor value has the constant magnitude and rotating phase angle. This calculated phasor values are used for the disturbance or fault identification in the power system based on Total Vector Error (TVE). The %TVE-based fault identification is more effective, because the TVE value is calculated with reference phasor value. If any fault/disturbance occurs or frequency changes then %TVE value changes. This change in TVE value is reflected in the calculation of the next sample (1/f.*N sec), giving the advantage to this method as compared to the other magnitude-based fault identification systems. Normally with the phasor calculation large data is produced, which requires large memory for the storage of this data and makes the analysis difficult. To avoid large data storage system conditional-based data storage system is proposed, where the data is stored during only the disturbance conditions or at every one second. With this technique, the data to be stored is reduced and the analysis of this data also becomes simpler for the post disturbance and for future load prediction. The performance of the proposed method is evaluated in terms of accuracy of calculation and its implementation ability. The simulation results are as per the IEEE C37.118.1a2014 for the power system monitoring and fault identification.

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Effective monitoring of power system with phasor measurement unit and effective data storage system

Cited by 3 publications

References 21 publications

Investigation of linear models for control of water flow and temperature in a water supply system

Investigation of linear models for control of water flow and temperature in a water supply system

Development and Implementation of Synchronized Phasor Measurements for Dynamic State Power System Monitoring and Fault Identification

Novel PMU Model for Dynamic State Disturbance Analysis with Effective Data Handling System

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