Zero-Voltage-Switching Sinusoidal Pulse Width Modulation Method for Three-phase Four-wire Inverter

ABSTRACT:  

A Zero-Voltage-Switching (ZVS) sinusoidal pulse width modulation (SPWM) method for three-phase four-wire inverter is proposed in order to achieve higher efficiency and power density. With the proposed modulation scheme, the ZVS operation of all switches including the main switches and the auxiliary switch can be realized. Besides, all seven switches operate at a fixed frequency. The ZVS SPWM scheme is introduced by considering the various combinations of the polarities in three-phase filter inductors currents and analysis of operating stages is presented. ZVS condition of the ZVS SPWM scheme is derived and discussions of ZVS condition for typical three-phase loads are also provided. In addition, the resonant parameters design and loss analysis are briefly investigated. Finally the proposed ZVS SPWM scheme is verified on a 10 kW inverter prototype with SiC MOSFET devices.

KEYWORDS:

1.      Zero-Voltage-Switching (ZVS)

2.      Sinusoidal pulse width modulation (SPWM)

3.      Three-phase four-wire inverter

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Fig. 1. ZVS three-phase four-wire inverter.

EXPECTED SIMULATION RESULTS:

(a)                                                                                              (b)

(c)                                                                                                (d)

Fig. 2. Three-phase load voltages and filter inductors currents of the ZVS inverter under balanced resistive load: (a) Three-phase load voltage, (b) load voltage and filter inductor current of phase A, (c) load voltage and filter inductor current of phase B, and (d) load voltage and filter inductor current of phase C.

(a)                                                                                                (b)

(c)                                                                                                   (d)

Fig. 3. Three-phase load voltages and filter inductors currents of the ZVS inverter under unbalanced resistive load: (a) Three-phase load voltage, (b) load voltage and filter inductor current of phase A, (c) load voltage and filter inductor current of phase B, and (d) load voltage and filter inductor current of  phase C.

(a)                                                                                           (b)

(c)                                                           (d)

Fig. 4. Three-phase load voltages and filter inductors currents of the ZVS inverter under unbalanced inductive load: (a) Three-phase load voltage, (b)  load voltage and filter inductor current of phase A, (c) load voltage and filter inductor current of phase B, and (d) load voltage and filter inductor current of phase C.

CONCLUSION:

A ZVS SPWM method combining with aligned turn on gate signals and extra short circuit stage is proposed for three-phase four-wire inverter. The generalized ZVS condition of the ZVS SPWM scheme is derived and the discussions of ZVS condition for some typical three-phase loads are provided. For balanced resistive load, balanced inductive load and unbalanced resistive load, short circuit stage is required. The short circuit stage may not be needed during several intervals for some kinds of unbalanced inductive load. The estimated loss analysis show that significant efficiency advantages can be obtained by ZVS three-phase four-wire inverter at high switching frequency in comparison with the hard switching three-phase four-wire inverter.

The ZVS turn-on of all switches, including the main switches and auxiliary switch under both balanced and unbalanced resistive load are achieved in the complete fundamental period with experimental verification. Besides, the ZVS SPWM inverter shows significant efficiency advantage. The measured highest conversion efficiency of the ZVS SPWM inverter is 98.3 % and 1.7 % higher than that of the hard switching inverter. At full load, the ZVS SPWM inverter has 2.1 % higher efficiency than the hard switching inverter.

REFERENCES:

[1] M. E. Fraser, C. D. Manning and B. M. Wells, “Transformerless four-wire PWM rectifier and its application in AC-DC-AC converters, ” in IEE Proceedings - Electric Power Applications, vol. 142, no. 6, pp. 410-416, Nov 1995.

[2] M. Dai, M. N. Marwali, J. W. Jung and A. Keyhani, “A Three-Phase Four-Wire Inverter Control Technique for a Single Distributed Generation Unit in Island Mode,” in IEEE Transactions on Power Electronics, vol. 23, no. 1, pp. 322-331, Jan. 2008.

[3] E. L. L. Fabricio, S. C. S. Júnior, C. B. Jacobina and M. B. de Rossiter Corrêa, “Analysis of Main Topologies of Shunt Active Power Filters Applied to Four-Wire Systems,” in IEEE Transactions on Power Electronics, vol. 33, no. 3, pp. 2100-2112, March 2018.

[4] H. Zhang, C. da Sun, Z. x. Li, J. Liu, H. y. Cao and X. Zhang, “Voltage Vector Error Fault Diagnosis for Open-Circuit Faults of Three-Phase Four-Wire Active Power Filters,” in IEEE Transactions on Power Electronics, vol. 32, no. 3, pp. 2215-2226, March 2017.

[5] M. V. Manoj Kumar and M. K. Mishra, “Three-leg inverter-based distribution static compensator topology for compensating unbalanced and non-linear loads,” in IET Power Electronics, vol. 8, no. 11, pp. 2076-2084, 11 2015.

Artificial Neural Network based Dynamic Voltage Restorer for Improvement of Power Quality

ABSTRACT:  

Dynamic Voltage Restorer (DVR) is a custom power device used as an effective solution in protecting sensitive loads from voltage disturbances in power distribution systems. The efficiency of the control technique, that conducts the switching of the inverters, determines the DVR efficiency.Proportional-Integral-Derivative (PID) control is the general technique to do that. The power quality restoration capabilities of this controller are limited, and it produces significant amount of harmonics – all of which stems from this linear technique’s application for controlling non-linear DVR. As a solution, this paper proposes an Artificial Neural Network (ANN) based controller for enhancing restoration and harmonics suppression capabilities of DVR. A detailed comparison of Neural Network controller with PID driven  controller and Fuzzy logic driven controller is also illustrated, where the proposed controller demonstrated superior performance with a mere 13.5% Total Harmonic Distortion.

KEYWORDS:

1.      Power quality

2.      Dynamic Voltage Restorer (DVR)

3.      PID

4.      Fuzzy logic

5.      Artificial Neural Network (ANN)

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. Block diagram of the proposed DVR system to mitigate voltage

instabilities.

EXPECTED SIMULATION RESULTS:

Fig. 2. Three phase sag mitigation based on ANN controlled DVR. (a) Instantaneous voltage at stable condition; (b) Instantantaneous voltage when sag occurs; (c) Voltage required to mitigate voltage sag; (d) Output voltage of the inverter circuit; (e) Generated PWM for inverter; (f) Instantaneous voltage after voltage restoration.

Fig. 3. Restored Voltage Using (a) PID controller; (b) Fuzzy controller; (c) ANN controller; (d)THD comparison: the least THD can be seen at ANN based DVR, the range of the harmonics is also truncated by a huge amount by this method.

CONCLUSION:

DVRs are a popular choice for enhancing power quality in power systems, with an array of control system on offer to drive these devices. In this paper, application of ANN to operate DVR for providing better performance than existing systems to mitigate voltage sag, swell, and harmonics has been demonstrated. Problem statement and theoretical background, structure of the proposed method, training procedure of the ANN used have been described in detail. Simulation results showing the DVR performance during voltage sag have been presented. Comparison of the proposed method with the popular PID controller, and nonlinear Fuzzy controller has been carried out, where the proposed ANN controller appeared as the best option to restore system voltage while mitigating THD to the greatest extent.

REFERENCES:

[1] M. H. Bollen, R. Das, S. Djokic, P. Ciufo, J. Meyer, S. K. Rönnberg, et al., "Power quality concerns in implementing smart distribution-grid applications," IEEE Transactions on Smart Grid, vol. 8, pp. 391-399, 2017.

[2] V. Khadkikar, D. Xu, and C. Cecati, "Emerging Power Quality Problems and State-of-the-Art Solutions," IEEE Transactions on Industrial Electronics, vol. 64, pp. 761-763, 2017.

[3] X. Liang, "Emerging power quality challenges due to integration of renewable energy sources," IEEE Transactions on Industry Applications, vol. 53, pp. 855-866, 2017.

[4] T. Sutradhar, J. R. Pal, and C. Nandi, "Voltage Sag Mitigation by using SVC," International Journal of Computer Applications, vol. 71, 2013.

[5] F. M. Mahdianpoor, R. A. Hooshmand, and M. Ataei, "A new  approach to multifunctional dynamic voltage restorer implementation for emergency control in distribution systems," IEEE transactions on power delivery, vol. 26, pp. 882-890, 2011.

A Fuzzy Logic Control Method for MPPT of PV Systems

 ABSTRACT:  

Maximum power point trackers are so important in photovoltaic systems to increase their efficiency. Many methods have been proposed to achieve the maximum power that the PV modules are capable of producing under different weather conditions. This paper proposed an intelligent method for maximum power point tracking based on fuzzy logic controller.  The system consists of a photovoltaic solar module connected to a DC-DC Buck-boost converter. The system has been experienced under disturbance in the photovoltaic temperature and irradiation level. The simulation results show that the proposed maximum power tracker could track the maximum power accurately and successfully in all condition tested. Comparison of different performance parameters such as: tracking efficiency and response time of the system shows that the proposed method gives higher efficiency and better performance than the conventional perturbation and observation method.

SOFTWARE: MATLAB/SIMULINK

 CIRCUIT DIAGRAM:

Fig. 1: System used for simulation.

EXPECTED SIMULATION RESULTS:

Fig. 2: case 1: changing the solar radiation

Fig. 3: Case 1: performance of FLC method

Fig. 4: Case I: performance of P&O method

Fig, 5: Case 2: changing the solar radiation

Fig, 6: Case 2: performance of FLC method

Fig, 7: Case 2: performance of P&O method

Fig, 8: Changing the temperature

Fig, 9: Performance of FLC method

Fig, 10: Performance of P&O method

CONCLUSION:

Photovoltaic model using Matlab/STMULTNK and design of appropriate DC-DC buck-boost converter with a maximum power point tracking facility are presented in this paper. A new method for MPPT based fuzzy logic controller is presented and compared with the conventional P&O MPPT method. The models are tested under disturbance in both solar radiation and photovoltaic temperature. Simulation results show that the proposed method effectively tracks the maximum power point under different ambient conditions.The oscillation around MPP is decreased and the response is faster in compared with the conventional methods. Comparing the tracking efficiency of both methods indicates that the proposed method has a higher efficiency than the conventional P&O MPPT method.

REFERENCES:

[1] Jancarle L. Dos Santos, Fernando L. M. Antunes and Anis Chehab, "A Maximum Power Point Tracker for PV Systems Using a High Performance Boost Converter", Solar Energy, Issue 7, Vol. 80, pp. 772- 778,2005.

[2] Ting-Chung Yu and Tang-Shiuan Chien, "Analysis and Simulation of Characteristics and Maximum Power Point Tracking for Photovoltaic Systems", Conference,P prpo.c 1e3ed3i9n g- s1 3o4f4 ,PT aoiwpeeri, 2E0l0e9c.t ronics and Drive Systems

[3] Roberto Faranda, Sonia Leva, "Energy Comparison of MPPT techniques for PV Systems", Wseas Transctions on Power System, Issue 6, Vol. 3, pp. 446-455, June 2008.

[4] D. P. Hohm and M. E. Ropp, "Comparative Study of Maximum Power Point Tracking Algorithms using an experimental, programmable, maximum power point tracking test bed",P roceedings of Photovoltaic Specialists Conference ,pp. 1699 - 1702, USA,2000.

[5] Trishan Esram and Patrick 1. Chapman, "Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques", Energy ConverSion, Issue 2, Vol. 22, pp. 439 - 449, May 2007.

Performance Recovery of Voltage Source Converters with Application to Grid-connected Fuel Cell DGs

ABSTRACT:  

Most common types of distributed generation (DG) systems utilize power electronic interfaces and, in particular,  three-phase voltage source converters (VSCs) which are mainly  used to regulate active and reactive power delivered to the grid. The main drawbacks of VSCs originate from their nonlinearities, control strategies, and lack of robustness against uncertainties. In this paper, two time-scale separation redesign technique is proposed to improve the overall robustness of VSCs and address the issues of uncertainties. The proposed controller is applied to a grid-connected Solid Oxide Fuel Cell (SOFC) distributed generation system to recover the trajectories of the nominal system despite the presence of uncertainties. Abrupt changes in the input dc voltage, grid-side voltage, line impedance and PWM malfunctions are just a few uncertainties considered in our evaluations. Simulation results based on detailed model indicate that the redesigned system with lower filter gain (_) achieves more reliable performance in compare to the conventional current control scheme. The results also verified that the redesigned controller is quite successful in improving the startup and tracking responses along with enhancing the overall robustness of the system.

KEYWORDS:

1.      Power converters

2.      Solid oxide fuel cell (SOFC)

3.      Distributed generation (DG)

4.      Time-scale separation redesign

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Schematic diagram of a grid-connected SOFC power plant with redesigned controller.

EXPECTED SIMULATION RESULTS:

Fig. 2. Active (top) and reactive (bottom) output power in case 1 (input dc

voltage) uncertainty using PI and redesigned controller.

Fig. 3. Output voltage (top) and current (bottom) of each SOFC array in case

1 (input dc voltage) uncertainty using PI and redesigned controller.

Fig. 4. Active (top) and reactive (bottom) output power in case 2 (grid-side

voltage) uncertainty using PI and redesigned controller.

Fig. 5. d-axis (top) and q-axis (bottom) currents of the VSC in case 2 (gridside

voltage) uncertainty using PI and redesigned controller.

Fig. 6. Active (top) and reactive (bottom) output power in case 3.1 (line

resistance) uncertainty using PI and redesigned controller.

Fig. 7. Active (top) and reactive (bottom) output power in case 3.2 (line

inductance) uncertainty using PI and redesigned controller.

Fig. 8. Additive random Gaussian noises on duty ratio of phase a (top), b

(middle), and c (bottom) of the VSC.

Fig. 9. Active (top) and reactive (bottom) output power in case 4 (duty

ratio) uncertainty using PI and redesigned controller.

CONCLUSION:

This paper presents a new control technique based on two time-scale separation redesign for the VSC of a grid connected SOFC DG system. A three-phase VSC is used to regulate active and reactive power delivered to the grid. In addition, variations in the input dc voltage, line impedance, grid-side voltage and duty ratio are mathematically formulated as additive uncertainties based on the nonlinear model of the VSC. As a result, the proposed controller is able to address the issues of robustness and further enhance the system stability in the presence of uncertainties. The redesigned controller also presents a fast and accurate startup response and delivers superior decoupling performance as compared to the conventional PI controller. Moreover, the redesigned controller significantly reduces the maximum overshoot in the output power while the system with a conventional controller exhibits deterioration in the output response which leads to excessive current and voltage variations in the FC arrays.

REFERENCES:

[1] P. Kundur, Power System Stability and Control. New York, NY, USA:McGraw-Hill, 1994.

[2] R. Seyezhai and B. L. Mathur, “Modeling and control of a PEM fuel cell based hybrid multilevel inverter,” International Journal of Hydrogen Energy, vol. 36, pp. 15029-15043, 2011.

[3] T. Erfanmanesh and M. Dehghani, “Performance improvement in gridconnected fuel cell power plant: An LPV robust control approach,”

International Journal of Electrical Power & Energy Systems, vol. 67, pp. 306-314, 2015.

[4] S. A. Taher and S. Mansouri, “Optimal PI controller design for active power in grid-connected SOFC DG system,” International Journal of Electrical Power & Energy Systems, vol. 60, pp. 268-274, 2014.

[5] R. Teodorescu, M. Liserre, and P. Rodriguez, Grid Converters for Photovoltaic and Wind Power Systems. Hoboken, NJ, USA: John Wiley & Sons, 2011.