Design and Performance Analysis of Three-Phase Solar PV Integrated UPQC

ABSTRACT:

In this paper, the design and performance of a three phase solar PV (photovoltaic) integrated UPQC (PV-UPQC) are presented. The proposed system combines both the benefits of distributed generation and active power filtering. The shunt compensator of the PV-UPQC compensates for the load current harmonics and reactive power. The shunt compensator is also extracting maximum power from solar PV array by operating it at its maximum power point (MPP). The series compensator compensates for the grid side power quality problems such as grid voltage sags/swells by injecting appropriate voltage in phase with the grid voltage. The dynamic performance of the proposed system is simulated in Matlab-Simulink under a nonlinear load consisting of a bridge rectifier with voltage-fed load.

KEYWORDS:

1.      Power Quality

2.      DSTATCOM

3.      DVR

4.      UPQC

5.      Solar PV

6.      MPPT

SOFTWARE: MATLAB/SIMULINK

 CIRCUIT DIAGRAM:

Fig. 1. System Configuration PV-UPQC

 EXPECTED SIMULATION RESULTS:

Fig. 2. Performance PV-UPQC at steady state condition

Fig. 3. PCC Voltage Harmonic Spectrum and THD

Fig. 4. Load Voltage Harmonic Spectrum and THD

Fig. 5. Load Current Harmonic Spectrum and THD

Fig. 6. Grid Current Harmonic Spectrum and THD

Fig. 7. Performance PV-UPQC at varying irradiation condition

Fig. 8. Performance of PV-UPQC under voltage sag and swell conditions

CONCLUSION:

The dynamic performance of three-phase PV-UPQC has been analyzed under conditions of variable irradiation and grid voltage sags/swells. It is observed that PV-UPQC mitigates the harmonics caused by nonlinear and maintains the THD of grid voltage, load voltage and grid current under limits of IEEE-519 standard. The system is found to be stable under variation of irradiation from 1000𝑊/𝑚2 to 600𝑊/𝑚2. It can be seen that PV-UPQC is a good solution for modern distribution system by integrating distributed generation with power quality improvement.

REFERENCES:

[1] Y. Yang, P. Enjeti, F. Blaabjerg, and H. Wang, “Wide-scale adoption of photovoltaic energy: Grid code modifications are explored in the distribution grid,” IEEE Ind. Appl. Mag., vol. 21, no. 5, pp. 21–31, Sept 2015.

[2] B. Singh, A. Chandra and K. A. Haddad, Power Quality: Problems and Mitigation Techniques. London: Wiley, 2015.

[3] M. Bollen and I. Guo, Signal Processing of Power Quality Disturbances. Hoboken: Johm Wiley, 2006.

[4] P. Jayaprakash, B. Singh, D. Kothari, A. Chandra, and K. Al-Haddad, “Control of reduced-rating dynamic voltage restorer with a battery energy storage system,” IEEE Trans. Ind. Appl., vol. 50, no. 2, pp. 1295– 1303, March 2014.

[5] M. Badoni, A. Singh, and B. Singh, “Variable forgetting factor recursive least square control algorithm for DSTATCOM,” IEEE Trans. Power Del., vol. 30, no. 5, pp. 2353–2361, Oct 2015.

Neuro Fuzzy based controller for Power Quality Improvement

Neuro Fuzzy based controller for Power Quality Improvement

ABSTRACT:

Use of power electronic converters with nonlinear loads leads to power quality problems by producing harmonic currents and drawing reactive power. A shunt active power filter provides an elegant solution for reactive power compensation as well as harmonic mitigation leading to improvement in power quality. However, the shunt active power filter with PI type of controller is suitable only for a given load. If the load is varied, the proportional and integral gains are required to be fine tuned for each load setting. The present study deals with hybrid artificial intelligence controller, i.e. neuro fuzzy controller for shunt active power filter. The performance of neuro fuzzy controller over PI controller is examined and tabulated. The salvation of the problem is extensively verified with various loads and plotted the worst case out of them for the sustainability of the neuro fuzzy controller.

KEYWORDS:

1.      Active Power Filter

2.      Neuro Fuzzy Controller

3.      Back Propagation Algorithm

4.      Soft Computing

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig 1. Schematic Diagram of Shunt Active Power Filter

 EXPECTED SIMULATION RESULTS:

Fig 2. (a) Waveform of Load Current, Compensating Current, Source

Current and Source Voltage for Case V of Table1 (1kVA with α=60o) and

(b) Waveform of Source Voltage and in phase Source Current of Fig. (a) Reproduced

CONCLUSION:

The application of hybrid artificial intelligence technique on shunt active power filter is proved to be an eminent solution for the mitigation of harmonics and the compensation of reactive power. The hybrid artificial intelligence used here is the neuro fuzzy controller. It takes the linguistic inputs as a fuzzy logic controller and it adapts any situation in between the running of the program as the neural network. The simulation results states that the active power filter controller with neuro fuzzy controllers have been seen to eminently minimize harmonics in the source current when the load demands non sinusoidal current, irrespective of whether the load is fixed or variable when compared to PI Controller. Simultaneously, the power factor at source also becomes the unity, if the load demands reactive power. The neuro fuzzy controller is far superior to the PI controller for all the loads. In the present work, a range of values of the load is considered to robustly test the controllers. It has been demonstrated that neuro fuzzy controller offers more acceptable results over the PI controller. The neuro fuzzy controller, therefore, significantly improves the performance of a shunt active power filter.

 REFERENCES:

[1]   Laszlo Gyugyi, “Reactive Power Generation and Control by Thyristor Circuits”, IEEE Transactions on Industry Applications, vol. IA-15, no. 5, September/October 1979.

[2]   H. Akagi, Y. Kanazawa, and A. Nabae, “Instantaneous reactive power compensators comprising switching devices without energy storage components,” IEEE Transaction Industrial Applications, vol. IA-20, pp. 625-630, May/June 1984.

[3]   F. Z. Peng, H. Akagi, and A. Nabae, “A study of active power filters using quad series voltage source pwm converters for harmonic compensation,” IEEE Transactions on Power Electronics, vol. 5, no. 1, pp. 9–15, January 1990.

[4]   Conor A. Quinn, Ned Mohan, “Active Filtering of Harmonic Currents in Three-phase, Four-Wire Systems with Three-phase and Single-phase Non-Linear Loads”, IEEE-1992.

[5]   L. A. Morgan, J. W. Dixon, and R. R. Wallace, “A three-phase active power filter operating with fixed switching frequency for reactive power and current harmonic compensation,” IEEE Transactions on Industrial Electronics, vol. 42, no. 4, pp. 402–408, August 1995.

Artificial Neural Network based Three Phase Shunt Active Power Filter

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

BLOCK DIAGRAM:

Fig.1. Proposed system configuration block with SAPF

 EXPECTED SIMULATION RESULTS:

Fig.2. Source voltages

Fig.3. Unbalanced load voltages

Fig.4. Unbalanced load currents

 Fig.5. Simulation result for proposed system under non linear with

unbalance load condition

Fig.6. DC link voltage

 Fig.7. Active power

Fig.8. Reactive power

Fig.9. Power factor

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

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

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.

REFERENCES:

[1]   P. Kumar and D.K. Palwalia, “Decentralized autonomous hybrid renewable power generation”, Journal of Renew. Energy, pp. 1-18, 2015.

[2]   W. Dai, T. Huang, and N. Lin, “Design of single-phase shunt active power filter based on ANN”, IEEE Int. Symp. on Ind. Electron., pp. 770-774, 2007.

[3]   H. Akagi, Y. Kanazawa, and A. Nabae, “Instantaneous reactive power compensators comprising switching devices without energy storage components,” IEEE Trans. Ind. Applicat., vol. IA-20, pp. 625–630, 1984.

[4]   H. Akagi and A. Nabae, “The p-q theory in three-phase systems under nonsinusoidal conditions,” Eur. Trans. Elect. Power Eng., vol. 3, no. 1, pp. 27–31, 1993.

[5]   H. Akagi and H. Fujita, “A new power line conditioner for harmonic compensation in power systems,” IEEE Trans. Power Delivery, vol. 10, pp. 1570–1575, 1995.

Application of Neural Networks in Power Quality

Application of Neural Networks in Power Quality

ABSTRACT:

Use of power electronic converters with nonlinear loads produces harmonic currents and reactive power. A shunt active power filter provides an elegant solution to reactive power compensation as well as harmonic mitigation leading to improvement in power quality. However, the shunt active power filter with PI type of controller is suitable only for a given load. If the load is varying, the proportional and integral gains are required to be fine tuned for each load setting. The present study deals with neural network based controller for shunt active power filter. The performance of neural network controller evaluated and compared with PI controller.

KEYWORDS:

1.      Active Power Filter

2.      Neural Networks

3.      Back Propagation Algorithm

4.      Soft Computing.

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig 1. Schematic Diagram of Shunt Active Power Filter

EXPECTED SIMULATION RESULTS:

Fig 2. (a) Waveform of Load Current, Compensating Current, Source Current and Source Voltage for 1kVA with 􀄮=60º and (b) Waveform of Source Voltage and in the phase Source Current of Fig. (a)

CONCLUSION:

The active power filter controller with neural network based controller has been seen to eminently minimize harmonics in the source current when the load demands non sinusoidal current, irrespective of whether the load is fixed or varying. Simultaneously, the power factor at source also becomes the unity, if the load demands reactive power. Thus, neural network based controller is far superior to PI type of controller which requires fine tuning of Kp and Ki every time the load changes. In the present work, the performance of a range of values of the load is considered to robustly test the controller. It has been demonstrated that neural network based controller, therefore, significantly improves the performance of a shunt active power filter.

REFERENCES:

[1]   Laszlo Gyugyi, “Reactive Power Generation and Control by Thyristor Circuits”, IEEE Transactions on Industry Applications, vol. IA-15, no. 5, September/October 1979.

[2]   H. Akagi, Y. Kanazawa, and A. Nabae, “Instantaneous reactive power compensators comprising switching devices without energy storage components,” IEEE Transaction Industrial Applications, vol. IA-20, pp. 625-630, May/June 1984.

[3]   F. Z. Peng, H. Akagi, and A. Nabae, “A study of active power filters using quad series voltage source pwm converters for harmonic compensation,” IEEE Transactions on Power Electronics, vol. 5, no. 1, pp. 9–15, January 1990.

[4]   Conor A. Quinn, Ned Mohan, “Active Filtering of Harmonic Currents in Three-phase, Four-Wire Systems with Three-phase and Single-phase Non-Linear Loads”, IEEE-1992.

[5]   L. A. Morgan, J. W. Dixon, and R. R. Wallace, “A three-phase active power filter operating with fixed switching frequency for reactive power and current harmonic compensation,” IEEE Transactions on Industrial Electronics, vol. 42, no. 4, pp. 402–408, August 1995.