Interharmonics: basic concepts and techniques for their detection and measurement

Li, Chun; Xu, Wilsun; Tayjasanant, Thavatchai

doi:10.1016/s0378-7796(03)00070-1

Cited by 84 publications

(39 citation statements)

References 6 publications

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“…Several articles have addressed the problem of inter-harmonic sources, the impacts, measurement and mitigation techniques [18][19][20][21][22]. However, the difficulty has remained in accurately finding the inter-harmonic frequencies and magnitudes.…”

Section: Inter-harmonicmentioning

confidence: 99%

Tracking simultaneous time-varying power harmonic distortions using filter banks

Duque

Silveira

Baldwin

et al. 2010

2010 IEEE Industrial and Commercial Power Systems Technical Conference - Conference Record

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Abstract-Although it is well known that the Fourier analysis is only accurately applicable to steady-state waveforms, it is a widely used tool to study and monitor time-varying signals, such as are commonplace in electrical power systems. The disadvantages of the Fourier analysis, such as frequency spillover or problems due to sampling (data window) truncation can often be minimized by various windowing techniques, but they nevertheless exist. This paper demonstrates that it is possible to track and visualize amplitude and time-varying power systems harmonics, without frequency spillover caused by classical timefrequency techniques. This new tool allows for a clear visualization of time-varying harmonics, which can lead to better ways to track harmonic distortion and understand timedependent power quality parameters. It has been applied to extract the harmonic contents of a rolling mill. It also has the potential to assist with control and protection applications.

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Section: Inter-harmonicmentioning

confidence: 99%

Tracking simultaneous time-varying power harmonic distortions using filter banks

Duque

Silveira

Baldwin

et al. 2010

2010 IEEE Industrial and Commercial Power Systems Technical Conference - Conference Record

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“…The FFT is the main signal processing tool used to characterize the magnitude spectrum of the input signal (voltage or current). However, that nonparametric tool, used for spectrum analysis, has well-known problems when the sampling rate is not synchronous with the fundamental component or when the signal is distorted by the interharmonic component [28][29][30][31]. Both can lead to misinterpretation of the spectrum content.…”

Section: Real-time Resampling Techniquementioning

confidence: 99%

Smart signal processing for an evolving electric grid

Silva

Duque

Ribeiro

2015

EURASIP J. Adv. Signal Process.

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Electric grids are interconnected complex systems consisting of generation, transmission, distribution, and active loads, recently called prosumers as they produce and consume electric energy. Additionally, these encompass a vast array of equipment such as machines, power transformers, capacitor banks, power electronic devices, motors, etc. that are continuously evolving in their demand characteristics. Given these conditions, signal processing is becoming an essential assessment tool to enable the engineer and researcher to understand, plan, design, and operate the complex and smart electronic grid of the future. This paper focuses on recent developments associated with signal processing applied to power system analysis in terms of characterization and diagnostics. The following techniques are reviewed and their characteristics and applications discussed: active power system monitoring, sparse representation of power system signal, real-time resampling, and time-frequency (i.e., wavelets) applied to power fluctuations.

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“…The necessary conditions for constrained local minima of L are (13) (14) where and is the order of harmonics considered (15) (16) By solving (13)- (16), is obtained for an optimum power factor within acceptable THD of current. 0 and 0 are the Kuhn-Tucker conditions to be satisfied at a relative minimum of the objective function.…”

Section: Lagrange Functionmentioning

confidence: 99%

“…By performing discrete Fourier transform (DFT) on the supply voltage and load current, RMS value of each harmonic component of voltage and current, in each phase is calculated. Interharmonic components, can also be detected by considering sampled data for multiple fundamental cycles [16]. However,these are not considered in this paper.…”

Section: Lagrange Functionmentioning

confidence: 99%

A Novel, DSP Based Algorithm for Optimizing the Harmonics and Reactive Power Under Non-Sinusoidal Supply Voltage Conditions

George

Agarwal

2005

IEEE Trans. Power Delivery

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Abstract-This paper presents a simple control algorithm for a shunt active filter for compensation of harmonics and reactive power under nonsinusoidal supply voltage conditions. Under nonsinusoidal supply conditions, any attempt to achieve unity power factor results in a nonsinusoidal current, which increases the total harmonic distortion (THD). On the other hand, attempt at getting harmonic free current may not yield unity power factor because of the harmonics present in the voltage waveform. The proposed algorithm optimizes this trade-off using the Lagrange multiplier technique and achieves the best compromise. It does not employ the normally used p-q theory and is applicable to both single phase and three phase systems. With the proposed technique, it is possible to obtain an optimized power factor satisfying the specified THD limit. The algorithm has been tested under various supply and load conditions using MATLAB simulations and validated with an experimental prototype based on DSP TMS320LF2407A.

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Interharmonics: basic concepts and techniques for their detection and measurement

Cited by 84 publications

References 6 publications

Tracking simultaneous time-varying power harmonic distortions using filter banks

Tracking simultaneous time-varying power harmonic distortions using filter banks

Smart signal processing for an evolving electric grid

A Novel, DSP Based Algorithm for Optimizing the Harmonics and Reactive Power Under Non-Sinusoidal Supply Voltage Conditions

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