This work describes artificial neural network (ANN) based control algorithm for three phase three wire shunt active power filter (SAPF) to compensate harmonics and improve power quality. System consists of three phase insulated gate bipolar transistors IGBT based current controlled voltage source inverter (CC-VSI), series coupling inductor and self supported DC bus. Increasing application of non-linear loads causes power quality problem. SAPF is one of the possible configurations to improve power quality. Traditional SAPF have PLL based unit template generator for extraction of fundamental signal. Traditional PLL needs to be tuned to obtain optimal performance for frequency estimation. It requires initial assumptions for fundamental frequency and minimum frequency. With varying frequency, it can’t be dynamically tuned for optimal performance. A new ANN based fundamental extraction based on Lavenberg Marquardt back propagation algorithm is proposed. Proposed SAPF is modeled in Simulink environment. Simulated results show the capability of proposed system.

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Artificial Neural Network based Three Phase Shunt
Active Power Filter
ABSTRACT:
This work describes artificial neural network (ANN) based control algorithm for three phase
three wire shunt active power filter (SAPF) to compensate harmonics and improve power
quality. System consists of three phase insulated gate bipolar transistors IGBT based current
controlled voltage source inverter (CC-VSI), series coupling inductor and self supported DC bus.
Increasing application of non-linear loads causes power quality problem. SAPF is one of the
possible configurations to improve power quality. Traditional SAPF have PLL based unit
template generator for extraction of fundamental signal. Traditional PLL needs to be tuned to
obtain optimal performance for frequency estimation. It requires initial assumptions for
fundamental frequency and minimum frequency. With varying frequency, it can’t be
dynamically tuned for optimal performance. A new ANN based fundamental extraction based on
Lavenberg Marquardt back propagation algorithm is proposed. Proposed SAPF is modeled in
Simulink environment. Simulated results show the capability of proposed system.
KEYWORDS:
1. Shunt Active Power Filter
2. Artificial Neural Networks
3. Indirect Current Control Technique
4. Power Quality
SOFTWARE: MATLAB/SIMULINK

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BLOCK DIAGRAM:
Fig.1. Proposed system configuration block with SAPF

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EXPECTED SIMULATION RESULTS:
Fig.2. Source voltages
Fig.3. Unbalanced load voltages
Fig.4. Unbalanced load currents

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Fig.5. Simulation result for proposed system under non linear with
unbalance load condition
Fig.6. DC link voltage

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Fig.7. Active power
Fig.8. Reactive power
Fig.9. Power factor

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Fig.10. Harmonic spectrum of load current before compensation for three phase SAPF with non
linear load

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Fig.11. Harmonic spectrum of source currents (phase a, phase b phase c respectively) after
compensation for ANN based three phase APF with non linear load
Fig.12. Harmonic spectrum of source currents (phase a) after compensation for ANN based three
phase APF with non linear load with unbalance

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CONCLUSION:
ANN based phase-locking scheme has been proposed in this paper to control three phase-three
wire shunt APFs. Widrow-Hoff weights updating algorithm has been incorporated to reduce
calculation time in estimation of harmonic components. To validate effectiveness of proposed
approach for real-time applications, indirect current control theory based controller has been
developed. Design parameters of power circuit and control circuit have been calculated and
robustness of proposed system has been established with Matlab/Simulink. Simulation result and
spectral response show that, obtained source current THDs is below 5% as prescribed by IEEE-
519 standard. Dynamic performance of proposed approach has been found satisfactory under
sudden change in load and frequency.
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