Chebyshev Functional Expansion Based Artificial Neural Network Controller for Shunt Compensation

Three-phase four-wire (TPFW) distribution systems are prone to various power quality (PQ) issues, such as voltage fluctuations, poor power factor, unbalanced load conditions, and the presence of harmonics in current. Mitigation of these PQ problems using appropriate shunt compensator requires advanc...

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Published in:IEEE transactions on industrial informatics Vol. 14; no. 9; pp. 3792 - 3800
Main Authors: Chittora, Prakash, Singh, Alka, Singh, Madhusudan
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.09.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive control
Algorithm design and analysis
Algorithms
Approximation algorithms
Artificial neural networks
Chebyshev approximation
Chebyshev polynomial (<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> ChP </tex-math> </inline-formula> </named-content>)
Compensation
Control algorithms
Converters
Electric potential
Informatics
Neural networks
nonlinear systems
Power factor
Power quality
power quality (PQ)
Reactive power
shunt compensation
Variations
Wire
ISSN:1551-3203, 1941-0050
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Abstract Three-phase four-wire (TPFW) distribution systems are prone to various power quality (PQ) issues, such as voltage fluctuations, poor power factor, unbalanced load conditions, and the presence of harmonics in current. Mitigation of these PQ problems using appropriate shunt compensator requires advanced control algorithms for control of three-phase voltage source converters (VSC) in a distribution system. In this paper, Chebyshev functional expansion based artificial neural network ( ChANN ) algorithm for shunt compensation using distribution static compensator (DSTATCOM) is proposed. The parameters of ChANN are trained in real time. Implementation results with linear and nonlinear loads are demonstrated on a prototype hardware designed and developed using dSPACE 1104, current and voltage sensors for the realization of DSTATCOM for TPFW system. A zigzag transformer is used along with conventional three-phase, three-wire (TPTW) DSTATCOM to reduce its overall rating. Suitable comparisons with conventional control techniques are also mentioned.
AbstractList Three-phase four-wire (TPFW) distribution systems are prone to various power quality (PQ) issues, such as voltage fluctuations, poor power factor, unbalanced load conditions, and the presence of harmonics in current. Mitigation of these PQ problems using appropriate shunt compensator requires advanced control algorithms for control of three-phase voltage source converters (VSC) in a distribution system. In this paper, Chebyshev functional expansion based artificial neural network ( ChANN ) algorithm for shunt compensation using distribution static compensator (DSTATCOM) is proposed. The parameters of ChANN are trained in real time. Implementation results with linear and nonlinear loads are demonstrated on a prototype hardware designed and developed using dSPACE 1104, current and voltage sensors for the realization of DSTATCOM for TPFW system. A zigzag transformer is used along with conventional three-phase, three-wire (TPTW) DSTATCOM to reduce its overall rating. Suitable comparisons with conventional control techniques are also mentioned.
Author Singh, Madhusudan
Chittora, Prakash
Singh, Alka
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SubjectTerms Adaptive control
Algorithm design and analysis
Algorithms
Approximation algorithms
Artificial neural networks
Chebyshev approximation
Chebyshev polynomial (<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> ChP </tex-math> </inline-formula> </named-content>)
Compensation
Control algorithms
Converters
Electric potential
Informatics
Neural networks
nonlinear systems
Power factor
Power quality
power quality (PQ)
Reactive power
shunt compensation
Variations
Wire
Title Chebyshev Functional Expansion Based Artificial Neural Network Controller for Shunt Compensation
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