Harmonic analysis in integrated energy system based on compressed sensing

Yang, Ting; Pen, Haibo; Wang, Dan; Wang, Zhao-xia

doi:10.1016/j.apenergy.2015.12.058

Cited by 20 publications

(6 citation statements)

References 27 publications

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“…The indeterminate system of equations is solved by a unique method called the spectral projected gradient with fundamental filter (SPG-FF). Finally, a signal reconstruction error of 1.8% is obtained [21].…”

Section: Related Workmentioning

confidence: 99%

Compressed Sensing Technique for the Localization of Harmonic Distortions in Electrical Power Systems

Amaya

Inga

2022

Sensors

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The present work proposes to locate harmonic frequencies that distort the fundamental voltage and current waves in electrical systems using the compressed sensing (CS) technique. With the compressed sensing algorithm, data compression is revolutionized, a few samples are taken randomly, a measurement matrix is formed, and according to a linear transformation, the signal is taken from the time domain to the frequency domain in a compressed form. Then, the inverse linear transformation is used to reconstruct the signal with a few sensed samples of an electrical signal. Therefore, to demonstrate the benefits of CS in the detection of harmonics in the electrical network of this work, power quality analyzer equipment (commercial) is used. It measures the current of a nonlinear load and issues its results of harmonic current distortion (THD-I) on its screen and the number of harmonics detected in the network; this equipment acquires the data based on the Shannon–Nyquist theorem taken as a standard of measurement. At the same time, an electronic prototype senses the current signal of the nonlinear load. The prototype takes data from the current signal of the nonlinear load randomly and incoherently, so it takes fewer samples than the power quality analyzer equipment used as a measurement standard. The data taken by the prototype are entered into the Matlab software via USB, and the CS algorithm run and delivers, as a result, the harmonic distortions of the current signal THD-I and the number of harmonics. The results obtained with the compressed sensing algorithm versus the standard measurement equipment are analyzed, the error is calculated, and the number of samples taken by the standard equipment and the prototype, the machine time, and the maximum sampling frequency are analyzed.

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Section: Related Workmentioning

confidence: 99%

Compressed Sensing Technique for the Localization of Harmonic Distortions in Electrical Power Systems

Amaya

Inga

2022

Sensors

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“…The attraction degree is related to distance. Farther the distance is, less the attractive there will be 28‐30 . In the optimal firefly population, the operation of the individual firefly needs to meet some basic characteristics.…”

Section: A Bilevel Collaborative Optimization Model For Integrated Energy Systems Considering Source‐load Uncertaintiesmentioning

confidence: 99%

Study on bi‐level multi‐objective collaborative optimization model for integrated energy system considering source‐load uncertainty

Tan

et al. 2021

Energy Science & Engineering

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The uncertainty of both the generation side and the user side brings certain impacts on the source‐load coordinated operation of integrated energy system (IES). At first, the source‐load characteristics of the IES with large‐scale distributed energy is analyzed. Secondly, considering lower operating cost and higher renewable energy consumption rate, a bilevel optimization model of the source‐load coordination based on the IES operation structure is established, which considers the uncertainty of both the generation side, such as wind and photovoltaic (PV) power output, and the load side. The robust optimization theory and stochastic chance‐constrained programming theory are introduced to establish the upper layer and the lower layer models of the IES. Besides, the firefly algorithm is used to design the solution process of the bilevel optimization model. The results show that the uncertainty of the wind power, PV power, and the load are positively correlated with the comprehensive operation cost. Also, based on the full consideration of the bilevel uncertainties, the system operation cost is significantly reduced. Meanwhile, the improvement of the confidence level of the objective function and constraint conditions will enhance the optimistic value of the comprehensive operation cost of the system, which means gaining higher reliability by sacrificing partial system benefits. Overall, the bilevel optimization model considering the source‐load uncertainty can both improve the renewable energy consumption rate and reduce the comprehensive operation cost of the IES system.

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“…Inductive current transformers (CTs) are one of the most popular devices used in the power system to convert high values of currents into a measurable level for metering and protection apparatus. Nonlinear loads connected to the power grid cause a distortion of the sinusoidal currents and voltages [1][2][3][4]. The advantage of Ref.…”

Section: Introductionmentioning

confidence: 99%

Understanding the Frequency Characteristics of Current Error and Phase Displacement of the Corrected Inductive Current Transformer

Stano

Kaczmarek

2022

Energies

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The paper presents investigations and analysis of the parameters of the magnetic part of the equivalent circuit of the inductive CT in the frequencies range from 50 Hz to 5 kHz. Therefore, a measuring circuit used to determine the values of the transverse branch elements was developed. The research performed helps to understand the obtained values of the frequency characteristics of the current error and phase displacement of the corrected inductive current transformer. Moreover, the vectorial diagrams for the 1st, 20th and 100th harmonics are provided with consideration of the influence of the applied turns number correction of the secondary winding. The obtained results show that the increase in the frequency of transformed higher harmonics may cause a decrease in the values of the current error and phase displacement for the non-corrected inductive current transformer. However, if the number of turns of the secondary winding is corrected, the behavior is reversed, where the values of the current error are higher with increased frequency. In the paper, the influence of the self-generation phenomenon of the low-order harmonics is also considered.

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Harmonic analysis in integrated energy system based on compressed sensing

Cited by 20 publications

References 27 publications

Compressed Sensing Technique for the Localization of Harmonic Distortions in Electrical Power Systems

Compressed Sensing Technique for the Localization of Harmonic Distortions in Electrical Power Systems

Study on bi‐level multi‐objective collaborative optimization model for integrated energy system considering source‐load uncertainty

Understanding the Frequency Characteristics of Current Error and Phase Displacement of the Corrected Inductive Current Transformer

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