Separating low-frequency electromechanical modes from spurious modes in ambient data analysis by means of modal stabilization diagrams

Reconstruction of realistic economic data often causes social economists to analyze the underlying driving factors in time-series data or to study volatility. The intrinsic complexity of time-series data interests and attracts social economists. This paper proposes the bilateral permutation entropy (BPE) index method to solve the problem based on partly ensemble empirical mode decomposition (PEEMD), which was proposed as a novel data analysis method for nonlinear and nonstationary time series compared with the T-test method. First, PEEMD is extended to the case of gold price analysis in this paper for decomposition into several independent intrinsic mode functions (IMFs), from high to low frequency. Second, IMFs comprise three parts, including a high-frequency part, low-frequency part, and the whole trend based on a fine-to-coarse reconstruction by the BPE index method and the T-test method. Then, this paper conducts a correlation analysis on the basis of the reconstructed data and the related affected macroeconomic factors, including global gold production, world crude oil prices, and world inflation. Finally, the BPE index method is evidently a vitally significant technique for time-series data analysis in terms of reconstructed IMFs to obtain realistic data.

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Use of ARMA Block Processing for Estimating Stationary Low-Frequency Electromechanical Modes of Power Systems

IEEE Power Engineering Review ◽

10.1109/mper.2002.4311824 ◽

2002 ◽

Vol 22 (11) ◽

pp. 57-57 ◽

Cited By ~ 4

Author(s):

R. W. Wies ◽

J. W. Pierre ◽

D. J. Trudnowski

Keyword(s):

Power Systems ◽

Low Frequency ◽

Block Processing ◽

Electromechanical Modes

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Ambient data analysis for robust and efficient structural identification

10.1117/12.816123 ◽

2009 ◽

Author(s):

Jian Zhang ◽

Franklin Moon ◽

Ahmet Aktan

Keyword(s):

Data Analysis ◽

Structural Identification ◽

Ambient Data

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Effects of sediment parameters on data analysis of low‐frequency beamformed bottom‐propagating modes

The Journal of the Acoustical Society of America ◽

10.1121/1.2023219 ◽

1986 ◽

Vol 79 (S1) ◽

pp. S40-S40

Author(s):

G. E. Ioup ◽

M. F. Werby ◽

G. J. Tango

Keyword(s):

Data Analysis ◽

Low Frequency

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Effective damping of local low frequency oscillations in power systems integrated with bulk PV generation

Protection and Control of Modern Power Systems ◽

10.1186/s41601-021-00219-6 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Ahmed Hesham Abd El-Kareem ◽

Mohamed Abd Elhameed ◽

Mahmoud M. Elkholy

Keyword(s):

Power Systems ◽

Objective Function ◽

Damping Ratio ◽

Low Frequency ◽

Synchronous Generator ◽

Synchronous Generators ◽

Local Modes ◽

Low Frequency Oscillations ◽

Electromechanical Modes ◽

System Stabilizer

AbstractHigh penetration of renewable sources into conventional power systems results in reduction of system inertia and noticeable low-frequency oscillations (LFOs) in the rotor speed of synchronous generators. In this paper, we propose effective damping of LFOs by incorporating a supplementary damping controller with a photovoltaic (PV) generating station, where the parameters of this controller are coordinated optimally with those of a power system stabilizer (PSS). The proposed method is applied to damp local electromechanical modes by studying a system comprising a synchronous generator and a PV station connected to an infinite bus. The PV station is modeled following the instructions of the Western Electricity Coordinating Council. The problem is modeled as an optimization problem, where the damping ratio of the electromechanical modes is designed as the objective function. Constraints including upper and lower limits of decision parameters and damping ratio of other modes are considered by imposing penalties on the objective function. Different optimization algorithms are used to pursue the optimal design, such as political, improved gray wolves and equilibrium optimizers. The results validate the effectiveness of the proposed controller with PSS in damping local modes of oscillations.

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Mode identification method of low-frequency oscillation for power system based on ambient data

COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering ◽

10.1108/compel-10-2020-0337 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Hong-Yan Yan ◽

Jin Kwon Hwang

Keyword(s):

Power System ◽

Curve Fitting ◽

Low Frequency ◽

Modal Identification ◽

Measurement Unit ◽

Frequency Oscillation ◽

Low Frequency Oscillation ◽

Content Type ◽

Identification Method ◽

Ambient Data

Purpose The purpose of this paper is to improve the online monitoring level of low-frequency oscillation in the power system. A modal identification method of discrete Fourier transform (DFT) curve fitting based on ambient data is proposed in this study. Design/methodology/approach An autoregressive moving average mathematical model of ambient data was established, parameters of low-frequency oscillation were designed and parameters of low-frequency oscillation were estimated via DFT curve fitting. The variational modal decomposition method is used to filter direct current components in ambient data signals to improve the accuracy of identification. Simulation phasor measurement unit data and measured data of the power grid proved the correctness of this method. Findings Compared with the modified extended Yule-Walker method, the proposed approach demonstrates the advantages of fast calculation speed and high accuracy. Originality/value Modal identification method of low-frequency oscillation based on ambient data demonstrated high precision and short running time for small interference patterns. This study provides a new research idea for low-frequency oscillation analysis and early warning of power systems.

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