Independent Component Analysis Techniques for Power System Load Estimation

2005 ◽  
pp. 287-317 ◽  
Author(s):  
Dagmar Niebur ◽  
Ekrem Gursoy ◽  
Huaiwei Liao
Keyword(s):  
Independent Component Analysis ◽  
Power System ◽  
Component Analysis ◽  
Independent Component ◽  
Load Estimation ◽  
System Load ◽  
Analysis Techniques

MODEL-FREE FUNCTIONAL MRI ANALYSIS USING TOPOGRAPHIC INDEPENDENT COMPONENT ANALYSIS

2004 ◽  
Vol 14 (04) ◽  
pp. 217-228 ◽  
Author(s):  
ANKE MEYER-BÄSE ◽  
OLIVER LANGE ◽  
AXEL WISMÜLLER ◽  
HELGE RITTER
Keyword(s):  
Independent Component Analysis ◽  
Slight Modification ◽  
Component Analysis ◽  
Independent Component ◽  
Self Organizing Map ◽  
Analysis Techniques ◽  
Model Free ◽  
Temporal Domain ◽  
Different Types ◽  
Fmri Analysis

Data-driven fMRI analysis techniques include independent component analysis (ICA) and different types of clustering in the temporal domain. Since each of these methods has its particular strengths, it is natural to look for an approach that unifies Kohonen's self-organizing map and ICA. This is given by the topographic independent component analysis. While achieved by a slight modification of the ICA model, it can be at the same time used to define a topographic order (clusters) between the components, and thus has the usual computational advantages associated with topographic maps. In this contribution, we can show that when applied to fMRI analysis it outperforms FastICA.

Data partitioning and independent component analysis techniques applied to fMRI

2004 ◽  
Author(s):  
Axel Wismueller ◽  
Anke Meyer-Base ◽  
Oliver Lange ◽  
Thomas D. Otto ◽  
Dorothee Auer
Keyword(s):  
Independent Component Analysis ◽  
Component Analysis ◽  
Data Partitioning ◽  
Independent Component ◽  
Analysis Techniques

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

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.

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