Application of PI, fuzzy logic and ANN in improvement of power quality using UPQC

Kumar, K. S. Ravi; Sastry, Srikanth

doi:10.1049/cp.2011.0381

Cited by 6 publications

(2 citation statements)

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“…The improvement of power quality can be achieved by using the UPQC with Fuzzy Logic Controller (FLC) and Artificial Neural Network (ANN) controller with respect to the conventional proportional integral (PI) controller. The better response time and derivation of compensation signals can be reduces the significantly with improved accuracy (Kumar and Sastry, 2011).…”

Section: Introductionmentioning

confidence: 99%

Novel Three-phase Four-wire UPQC Topology Using Adaptive-network-based Fuzzy Inference System for Voltage Sag Compensation

Indumathi¹,

Padmapriyadharishini²,

Ramakrishnan³

2016

RJASET

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This Study Proposes the novel four wire UPQC topology for Non-linear load and three-phase fault compensation. The electrical power quality is affected by many factors like harmonic pollution due to non-linear loads such as large thyristor power converters, rectifiers and the voltage/current flickering due to arc furnaces and also the sag and swell creation due to the switching of the loads. To overcome the above mentioned problems use of a combined system of shunt and active series filters like Unified Power Quality Conditioner (UPQC) topology. This device contains the integration of a shunt active filter together with a series active filter in a back to back configuration to simultaneously compensate the supply voltage and the load current. Also, it is used to mitigate any type of voltage and current fluctuations and power factor correction in a power distribution network. In this study a novel design of UPQC proposed for voltage sag compensation by using Adaptive Network based fuzzy inference system (ANFIS). This proposed controller has been provided the dynamic control of shunt and series converter operation. It has the combined operations of FL and Artificial Neural Network (ANN) relative advantages and also a powerful processing tool with both advantages can be obtained by combining them together. The simulation results have verified by using MATLAB/SIMULINK environment.

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Section: Introductionmentioning

confidence: 99%

Novel Three-phase Four-wire UPQC Topology Using Adaptive-network-based Fuzzy Inference System for Voltage Sag Compensation

Indumathi¹,

Padmapriyadharishini²,

Ramakrishnan³

2016

RJASET

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“…In another development a control algorithm based on wavelet transform for UPQC to suppress current harmonics and voltage sags is proposed [ 17 ]. Subsequently in [ 18 ], the authors emphasize enhancement of power quality by using UPQC with fuzzy logic controller (FLC) and artificial neural network (ANN) controller on the conventional proportional-integral (PI) controller. In [ 19 ], the determination of voltage references for series-active power filter is done based on a robust three-phase digital phase locked loop (PLL) system using fuzzy regulator.…”

Section: Introductionmentioning

confidence: 99%

MATLAB Simulation of UPQC for Power Quality Mitigation Using an Ant Colony Based Fuzzy Control Technique

Kumarasabapathy

Manoharan

2015

The Scientific World Journal

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This paper proposes a fuzzy logic based new control scheme for the Unified Power Quality Conditioner (UPQC) for minimizing the voltage sag and total harmonic distortion in the distribution system consequently to improve the power quality. UPQC is a recent power electronic module which guarantees better power quality mitigation as it has both series-active and shunt-active power filters (APFs). The fuzzy logic controller has recently attracted a great deal of attention and possesses conceptually the quality of the simplicity by tackling complex systems with vagueness and ambiguity. In this research, the fuzzy logic controller is utilized for the generation of reference signal controlling the UPQC. To enable this, a systematic approach for creating the fuzzy membership functions is carried out by using an ant colony optimization technique for optimal fuzzy logic control. An exhaustive simulation study using the MATLAB/Simulink is carried out to investigate and demonstrate the performance of the proposed fuzzy logic controller and the simulation results are compared with the PI controller in terms of its performance in improving the power quality by minimizing the voltage sag and total harmonic distortion.

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A review on performance of artificial intelligence and conventional method in mitigating PV grid-tied related power quality events

Kow

Wong

Rajkumar

et al. 2016

Renewable and Sustainable Energy Reviews

115

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Application of PI, fuzzy logic and ANN in improvement of power quality using UPQC

Cited by 6 publications

References 0 publications

Novel Three-phase Four-wire UPQC Topology Using Adaptive-network-based Fuzzy Inference System for Voltage Sag Compensation

Novel Three-phase Four-wire UPQC Topology Using Adaptive-network-based Fuzzy Inference System for Voltage Sag Compensation

MATLAB Simulation of UPQC for Power Quality Mitigation Using an Ant Colony Based Fuzzy Control Technique

A review on performance of artificial intelligence and conventional method in mitigating PV grid-tied related power quality events

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