A Dynamic Synchrophasor Estimation Algorithm for Online Application

Mai, Ruikun; Fu, Ling; Kirby, Brian; Bo, Z.Q.

doi:10.1109/tpwrd.2009.2034293

Cited by 136 publications

(62 citation statements)

References 18 publications

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“…Maximally flat differentiators [11] and phasorlet [12] are other new methods for dynamic phasor estimation. Mai et al, [13]; Serna and Martin [14]; Serna [15] proposed modified forms of earlier methods.…”

Section: Introductionmentioning

confidence: 99%

Least square and Kalman based methods for dynamic phasor estimation: a review

Khodaparast

Khederzadeh

2017

Prot Control Mod Power Syst

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The characterization of sinusoidal signals with time varying amplitude and phase is useful and applicable for many fields. Therefore several algorithms have been suggested to estimate main aspects of these signals. Within no standard approach to test the properties of these algorithms, it seems to be helpful to discuss a large class of algorithms according to their properties. In this paper, six methods of estimating dynamic phasor have been reviewed and discussed which three of them are based on least square and others are based on Kalman filter. Taylor expansion is used as a first step and continued with least square or Kalman filter in accordance with the proposal observer of each method. The theoretical processes of these methods are briefly clarified. The characterizations have been made by some tests in time and frequency domains. The tests include amplitude step, phase step, frequency step, frequency response, total vector error, transient monitor, noise, sample number, computation time, harmonic and DC offset which build a framework to compare the different methods.

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Section: Introductionmentioning

confidence: 99%

Least square and Kalman based methods for dynamic phasor estimation: a review

Khodaparast

Khederzadeh

2017

Prot Control Mod Power Syst

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“…In particular, the step change in power signals is taken into account and the strategy for detection has been introduced to locate the step change. The phasor estimation is calculated using dynamic phasor estimator [12] with the adaptively selected initial estimations. Finally, based on a Taylor-expansion frequency model, frequency parameters of dynamic frequency model can be attained with the phase data of the estimated phasors by LSM.…”

Section: Iet Science Measurement and Technologymentioning

confidence: 99%

“…Then, higher-order phasor estimation can be obtained according to matrix-operation proposed in [12] ( (13)- (19) in [12]). …”

Section: Higher-order Phasor Estimation Based On Selected Initial Estmentioning

confidence: 99%

Precise algorithm for frequency estimation under dynamic and step‐change conditions

Han

et al. 2015

IET Science, Measurement & Technology

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To achieve fast-response frequency estimation under step-change dynamics as well as accurate frequency estimation under slowly varying dynamics, a dynamic-model-based frequency estimation with step-change detection (DFESD) algorithm is proposed in this study. In DFESD, the derivative of the initial phasor estimation, which is obtained from short-time Fourier transform and the first-order Taylor-expansion phasor model, is used to detect the step changes in signals. Then, the initial estimations are adaptively selected by the data-selection strategy to estimate the frequency, of which the estimation is based on a high-order Taylor-expansion model to express the dynamic characteristics in signal. DFESD is a Taylor-expansion-based algorithm and it avoids the states mixture of both pre-and post-step-change data within one long data window, so it can track the frequency accurately under slowly varying dynamics and give fast-response estimation under step-change dynamics. Performance of the proposed algorithm is evaluated by computer-simulated and electromagnetic transients including DC (EMTDC) generated signals, and the results prove the efficiency of DFESD for accurate or fast-response frequency estimation under various test cases.

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“…In this case the following multi-oscillation signal as used in [16] is added as additional oscillation components to all three phase voltage sources. The oscillation appears in the system for 0.5s from t = 0.4s to t = 0.9s.…”

Section: Figure 1 Test Circuitmentioning

confidence: 99%

Towards new measurements for dynamic control of future power grids

Liu

Kruger

Ponci

et al. 2012

2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings

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In this paper, we analyze and compare classical modeling and measurement methods like Park's transformation with the dynamic phasor concept and the corresponding calculation algorithms. The comparison aims at understanding the measurement performance of these approaches under low frequency oscillation, transient change, harmonic distortion and unbalance which are the usual transient and non-sinusoidal conditions in power systems and power electronics control. Based on this comparison we aim at analyzing and classifying the fitness of the different concepts for different control approaches and purposes in power grids. This work is a first step towards defining an appropriate concept for every level of control for future power grids with increasing complexity and dynamics.

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A Dynamic Synchrophasor Estimation Algorithm for Online Application

Cited by 136 publications

References 18 publications

Least square and Kalman based methods for dynamic phasor estimation: a review

Least square and Kalman based methods for dynamic phasor estimation: a review

Precise algorithm for frequency estimation under dynamic and step‐change conditions

Towards new measurements for dynamic control of future power grids

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