Placement of PMUs for tracking inter-area modes in the Mexican system

Calderon-Guizar, Jorge Guillermo

doi:10.1109/tdc-la.2012.6319135

Cited by 3 publications

(6 citation statements)

References 12 publications

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“…The location of the PMUs is determined through participation factor analysis in this study, which specifies generators with the highest participation factors in the critical modes [39]. Thus, it is seen that a minimum number of PMUs are used for the proposed CWTFT* method.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Thus, Shannon's entropy can be used to evaluate diversity of a wavelet coefficient matrix. Given the wavelet coefficient matrix , its Shannon's entropy as a function of and , denoted by , is calculated as follows: (39) where is the probability of calculated as follows: (40) Note that . In (40), is the th column of , and is the Euclidean norm of the vector as a measure of its energy.…”

Section: Optimizing the Wavelet-free Parametersmentioning

confidence: 99%

“…Fig. 6 shows the variation of Shannon's entropy , calculated using (39) and (40), with respect to . It is seen that the minimum Shannon's entropy is obtained for .…”

Section: A Experiments I-stable Scenariomentioning

confidence: 99%

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A Fourier Based Wavelet Approach Using Heisenberg’s Uncertainty Principle and Shannon’s Entropy Criterion to Monitor Power System Small Signal Oscillations

Hosseini

Amjady

Velayati

2015

IEEE Trans. Power Syst.

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This paper presents a novel approach to estimate modal parameters of power systems for monitoring and analyzing the embedded modes of small signal oscillations. The proposed approach applies continuous wavelet transform (CWT) to identify damping and frequency of critical modes based on its time-frequency localization capability. The CWT has modified Morlet function as its mother wavelet. A procedure is also presented to fine-tune settings of the modified Morlet function of the CWT based on Heisenberg's uncertainty principle and Shannon's entropy criterion. Additionally, high computational burden of the time-frequency methods is an important obstacle in online monitoring of power systems by these methods. To remedy this problem, the convolution integral of the CWT is calculated by efficient fast Fourier transform (FFT) routine in the proposed approach leading to a low computational burden. The proposed approach is compared with several other signal processing methods for modal identification of power systems. These comparisons illustrate effectiveness of the proposed approach, regarding run time, persistency against noise and estimation accuracy for online monitoring of small signal oscillations. Index Terms-Continuous wavelet transform (CWT), fastFourier transform (FFT), Heisenberg's uncertainty principle, modal identification, Shannon's entropy, small signal oscillations.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Optimizing the Wavelet-free Parametersmentioning

confidence: 99%

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A Fourier Based Wavelet Approach Using Heisenberg’s Uncertainty Principle and Shannon’s Entropy Criterion to Monitor Power System Small Signal Oscillations

Hosseini

Amjady

Velayati

2015

IEEE Trans. Power Syst.

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“…In order to better emphasize the suitability of the proposed methodology, Table 9 depicts a comparative study between the proposed approach and other approaches from the the previous studies 37,38,58 on the IEEE-39 test system. One can note the following:…”

Section: Comparative Studymentioning

confidence: 99%

“…Different approach reports for small‐signal assessment in a multi‐machine system by deposing a PMU on generations bus . Small‐signal stability assessment using the information from PMUs through Prony analysis that has been addressed in previous studies can successfully find electromechanical modes of oscillation for small‐signal stability analysis, the effect of noise on measured signal is not considered in any of the above mentioned studies, results obtained where signal from one PMU are used for Prony analysis, and each area of a network was studied separately. Also, this method suffers from a very time‐consuming process, which cannot be used practically in real‐dimensional power systems.…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective optimal PMUs placement for online assessment of small‐signal stability

Tarif

Amrane

Chabane

2019

Int Trans Electr Energ Syst

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Summary The current paper presents a multi‐objective approach for the optimal placement of phasor measurement units (PMUs) for small‐signal stability assessment of a power system. The proposed methodology is based on a multi‐signal Prony analysis of the voltage amplitude, voltage angle, and frequency signals measured by the PMUs. A Pareto Archive Differential Evolution (PADE) algorithm is used to determine the best location of PMUs minimizing the PMUs number and maximizing the signal‐to‐noise ratio (SNR) subject to full system constraints. The capability of the proposed approach has been demonstrated through several cases studies, where it gives an accurate estimation of electromechanical modes when confronted with modal analysis under various scenarios, disturbances, and measurement noise. Additionally, the PADE algorithm is compared with nondominated sorting approach (NSGA)‐III, multi‐objective differential evolution (MODE), and multi‐objective particle swarm optimization (MOPSO) algorithms, and the superiority of PADE algorithm for solving the optimal PMUs placement (OPP) problem is demonstrated.

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Power system coherency recognition and islanding: Practical limits and future perspectives

Chamorro

Gomez‐Diaz

Paternina

et al. 2022

IET Energy Syst Integration

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Electrical power systems are continuously upgrading into networks with a higher degree of automation capable of identifying and reacting to different events that may trigger undesirable situations. In power systems with decreasing inertia and damping levels, poorly damped oscillations with sustained or growing amplitudes following a disturbance may eventually lead to instability and provoke a major event such as a blackout. Additionally, with the increasing and considerable share of renewable power generation, unprecedented operational challenges shall be considered when proposing protection schemes against unstable electro-mechanical (e.g. ringdown) oscillations. In an emergency situation, islanding operations enable splitting a power network into separate smaller networks to prevent a total blackout. Due to such changes, identifying the underlying types of oscillatory coherency and the islanding protocols are necessary for a continuously updating process to be incorporated into the existing power system monitoring and control tasks. This paper examines the existing evaluation methods and the islanding protocols as well as proposes an updated operational guideline based on the latest dataanalytic technologies.

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Placement of PMUs for tracking inter-area modes in the Mexican system

Cited by 3 publications

References 12 publications

A Fourier Based Wavelet Approach Using Heisenberg’s Uncertainty Principle and Shannon’s Entropy Criterion to Monitor Power System Small Signal Oscillations

A Fourier Based Wavelet Approach Using Heisenberg’s Uncertainty Principle and Shannon’s Entropy Criterion to Monitor Power System Small Signal Oscillations

Multi‐objective optimal PMUs placement for online assessment of small‐signal stability

Power system coherency recognition and islanding: Practical limits and future perspectives

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