An identification method of harmonic source in the power system based on independent component analysis

2012 ◽  
Author(s):  
Shan Jiang ◽  
Minyou Chen ◽  
Hao Lin ◽  
Zhisheng Lv ◽  
Ang Fu
Keyword(s):  
Independent Component Analysis ◽  
Power System ◽  
Component Analysis ◽  
Independent Component ◽  
Identification Method ◽  
Harmonic Source

An Identification Method of Harmonic Source in the Power System Based on Independent Component Analysis

2013 ◽  
Vol 380-384 ◽  
pp. 4088-4093
Author(s):  
Shan Jiang ◽  
Min You Chen ◽  
Hao Lin ◽  
Zhi Sheng Lv ◽  
Ang Fu
Keyword(s):  
Independent Component Analysis ◽  
Power System ◽  
Harmonic Distortion ◽  
Component Analysis ◽  
Independent Component ◽  
Identification Method ◽  
Harmonic Voltage ◽  
Harmonic Source ◽  
Signal Sources ◽  
Mutually Independent

In this research, an identification method of harmonic source, based on independent component analysis, was proposed. An unknown harmonic source in the equivalent circuit of power system was regarded as the signal source in the independent component analysis. The known voltage and current of PCC were taken as observed quantities. The independent component analysis and the optimization algorithm were utilized to construct a matrix that could linearly transform voltage and current of PCC into mutually independent signal sources. The harmonic impedance and harmonic source of both the user side and system side were obtained. Then the contribution of users to the harmonic distortion at PCC could be identified. With a good anti-jamming property, this algorithm only needs a condition that variations in the harmonic voltage sources at system side and user side are independent to each other. Simulation results indicated the effectiveness of the method to identify the harmonic source of PCC.

Method based on independent component analysis for harmonic extraction from power system signals

2015 ◽  
Vol 119 ◽  
pp. 19-24 ◽  
Author(s):  
Danton D. Ferreira ◽  
Erick A. Nagata ◽  
Silvia C. Ferreira ◽  
José M. de Seixas ◽  
Carlos A. Duque ◽  
...  
Keyword(s):  
Independent Component Analysis ◽  
Power System ◽  
Component Analysis ◽  
Independent Component ◽  
Harmonic Extraction

An Independent Component Analysis Approach for Wide-Area Monitoring of Power System Disturbances

2020 ◽  
Vol 48 (6-7) ◽  
pp. 615-627
Author(s):  
José de Jesús Nuño Ayón ◽  
Jorge Luis García Sánchez ◽  
Eduardo Salvador Bañuelos Cabral ◽  
Julián Sotelo Castañón ◽  
María José Rodríguez Roblero
Keyword(s):  
Independent Component Analysis ◽  
Power System ◽  
Component Analysis ◽  
Independent Component ◽  
Wide Area ◽  
Analysis Approach ◽  
Wide Area Monitoring ◽  
Area Monitoring ◽  
Power System Disturbances

scholarly journals Multi-Harmonic Source Localization Based on Sparse Component Analysis and Minimum Conditional Entropy

Entropy ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. 65
Author(s):  
Du ◽  
Yang ◽  
Ma
Keyword(s):  
Independent Component Analysis ◽  
Distribution System ◽  
Conditional Entropy ◽  
Component Analysis ◽  
Independent Component ◽  
Minimum Condition ◽  
Harmonic Current ◽  
Sparse Component Analysis ◽  
System Node ◽  
Harmonic Source

Aiming at the fact that the independent component analysis algorithm requires more measurement points and cannot solve the problem of harmonic source location under underdetermined conditions, a new method based on sparse component analysis and minimum conditional entropy for identifying multiple harmonic source locations in a distribution system is proposed. Under the condition that the network impedance is unknown and the number of harmonic sources is undetermined, the measurement node configuration algorithm selects the node position to make the separated harmonic current more accurate. Then, using the harmonic voltage data of the selected node as the input, the sparse component analysis is used to solve the harmonic current waveform under underdetermination. Finally, the conditional entropy between the harmonic current and the system node is calculated, and the node corresponding to the minimum condition entropy is the location of the harmonic source. In order to verify the effectiveness and accuracy of the proposed method, the simulation was performed in an IEEE 14-node system. Moreover, compared with the results of independent component analysis algorithms. Simulation results verify the correctness and effectiveness of the proposed algorithm.

Extracting the transient events from power system signals by independent component analysis

2015 ◽  
Vol 26 (4) ◽  
pp. 884-900 ◽  
Author(s):  
Danton D. Ferreira ◽  
José M. de Seixas ◽  
Augusto S. Cerqueira ◽  
Carlos A. Duque ◽  
Math H. J. Bollen ◽  
...  
Keyword(s):  
Independent Component Analysis ◽  
Power System ◽  
Component Analysis ◽  
Independent Component ◽  
Transient Events

Integrated Kalman-Independent Component Analysis Method for Harmonic Current Estimation on an Interconnected Four Bus Simulated and Laboratory Model

2012 ◽  
Vol 13 (3) ◽  
Author(s):  
P. Supriya ◽  
P. Nambiar
Keyword(s):  
Independent Component Analysis ◽  
Power System ◽  
State Estimation ◽  
Component Analysis ◽  
Independent Component ◽  
Laboratory Model ◽  
Optimal Estimator ◽  
Current Estimation ◽  
Independent Component Analysis Method ◽  
Mixing Matrix

Abstract Wide use of non-linear loads results in harmonic propagation throughout the entire power system. The harmonics generated in the power system by the harmonic injection buses need to be properly measured and quantified using minimal information about the power system network. Independent Component Analysis (ICA) provides several algorithms for harmonic state estimation, some of which are more accurate at specific harmonic frequencies. In this paper, the best ICA algorithm for steady state performance (i.e. the algorithm with the least error) is chosen and the resulting mixing matrix is processed by a Kalman Filter which functions as an optimal estimator. The harmonic state estimation is implemented on a simulated four bus system and a laboratory four bus model is also wired and the results of the work are presented.

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