A New Variable-Speed Wind Energy Conversion System Using Permanent-Magnet Synchronous Generator and Z-Source Inverter

ABSTRACT:

With the growth of wind energy conversion systems (WECSs), various technologies are developed for them. Permanent-magnet synchronous generators (PMSGs) are used by these technologies due to special characteristics of PMSGs such as low weight and volume, high performance, and the elimination of the gearbox. In this paper, a new variable-speed WECS with a PMSG and Z-source inverter is proposed. Characteristics of Z-source inverter are used for maximum power tracking control and delivering power to the grid, simultaneously.  Two control methods are proposed for delivering power to the grid: Capacitor voltage control and dc-link voltage control. Operation of system with these methods is compared from the viewpoint of power quality and total switching device power (TSDP). In addition, TSDP, current ripple of inductor, performance, and total harmonic distortion of grid current of proposed system is compared with traditional wind energy system with a boost converter.

KEYWORDS:

1.      Maximum power point tracking (MPPT) control

2.      Permanent-magnet synchronous generator (PMSG)

3.      Wind energy conversion system (WECS)

4.      Z-source inverter

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Proposed PMSG-based WECS with Z-source inverter.

EXPECTED SIMULATION RESULTS:

Fig. 2. DC voltage and optimum rotor speed relation: simulated and approximated

and calculated (actual).

Fig. 3. Wind speed variation.

Fig. 4. PMSG rotor speed (capacitor voltage control).

Fig. 5. Maximum mechanical power of turbine and the extracted mechanical

power from turbine (capacitor voltage control).

Fig. 6. Capacitor voltage (capacitor voltage control).

Fig. 7. Active and reactive powers (capacitor voltage control).

Fig. 8. Active power delivered to the grid and extracted mechanical power

(capacitor voltage control).

Fig. 9. Inductor current of Z-source inverter (capacitor voltage control).

Fig. 10. Input voltage of Inverter (Vi ) (capacitor voltage control).

Fig. 11. PMSG rotor speed (dc-link voltage control).

Fig. 12. The maximum mechanical power of turbine and the extracted mechanical

power from turbine (dc-link voltage control).

Fig. 13. Active power delivered to the grid and extracted mechanical power

(dc-link voltage control).

Fig. 14. Capacitor voltage (dc-link voltage control).

Fig. 15. Input voltage of Inverter (Vi ) (dc-link voltage control).

Fig. 16. DC-link voltage across the rectifier.

Fig. 17. DC-link voltage across the Z-source inverter.

Fig. 18. Inductor current of Z-source inverter.

Fig. 19. Inductor current of Z-source inverter (zoomed).

Fig. 20. Grid current in proposed WECS.

Fig. 21. Spectra of grid current in proposed WECS.

Fig. 22. Inductor current of boost converter (zoomed).

Fig. 23. Inductor current of boost converter.

Fig. 24. Grid current in traditional WECS without dead time.

Fig. 25. Spectra of grid current in traditional WECS without dead time.

Fig. 26 Grid current in traditional WECS with dead time.

Fig. 27. Spectra of grid current in traditional WECS with dead time.

Fig. 28. Active power delivered to the grid in conventional and proposed WECSs.

Fig. 29. Efficiency of conventional and proposed WECSs.

CONCLUSION:

In this paper, a PMSG-based WECS with Z-source inverter is proposed. Z-source inverter is used for maximum power tracking control and delivering power to the grid, simultaneously. Compared to conventional WECS with boost converter, the number of switching semiconductors is reduced by one and reliability of system is improved, because there is no requirement for dead time in a Z-source inverter. For active power control, two control methods: capacitor voltage control and dc-link voltage control is proposed and compared. It is shown that with dc-link voltage control method, TSDP is increased only 6% compared to conventional system, but there is more power fluctuations compared to capacitor voltage control. With capacitor voltage control TSDP in increased 19% compared to conventional system. It was also shown that due to elimination of dead time, the THD of proposed system is reduced by 40% compared to conventional system by 5mS dead time. Finally, with same value of passive components, inductor current ripple is the same for both systems.

REFERENCES:

[1] E. Spooner and A. C. Williamson, “Direct coupled permanent magnet generators for wind turbine applications,” Inst. Elect. Eng. Proc., Elect. Power Appl., vol. 143, no. 1, pp. 1–8, 1996.

[2] N. Yamamura, M. Ishida, and T. Hori, “A simple wind power generating system with permanent magnet type synchronous generator,” in Proc. IEEE Int. Conf. Power Electron. Drive Syst., 1999, vol. 2, pp. 849–854.

[3] S. H. Song, S. Kang, and N. K. Hahm, “Implementation and control of grid connected AC–DC–AC power converter for variable speed wind energy conversion system,” Appl. Power Electron. Conf. Expo., vol. 1, pp. 154–158, 2003.

[4] A. M. Knight and G. E. Peters, “Simple wind energy controller for an expanded operating range,” IEEE Trans. Energy Convers., vol. 20, no. 2, pp. 459–466, Jun. 2005.

[5] T. Tafticht, K. Agbossou, A. Cheriti, and M. L. Doumbia, “Output power maximization of a permanent magnet synchronous generator based standalone wind turbine,” in Proc. IEEE ISIE 2006, Montreal, QC, Canada, pp. 2412–2416.

A Modified Active Power Control Scheme for Enhanced Operation of PMSG Based WGs

 ABSTRACT:

This paper emphasises the development of a simplified active power control scheme for enhanced operation of grid integrated permanent magnet synchronous generator (PMSG) based wind-driven generators (WGs). An active power reference generation scheme is proposed for the machine side converter (MSC) to inject active power into the grid even under grid disturbances, without violating system components rating. In this scheme, the controller employed for MSC adjusts the active power captured proportionate to the drop in the grid voltage upon considering wind speed and rotor speed. Furthermore, unlike dual vector control scheme, the grid side converter (GSC) controller is implemented in a positive synchronous frame (PSF) with the proposed current oscillation cancellation scheme to suppress the oscillations in dc-link voltage, active and reactive power of the grid and to obtain symmetrical sinusoidal grid current. Extensive analytical simulation has been carried out in PSCAD/ EMTDC to validate the superiority of proposed control scheme over the conventional schemes when WG is subjected to various grid disturbances. The reduced percentage of oscillation in the system parameters such as dc-link voltage and grid active power confirms the efficacy of the proposed method when compared with the conventional control techniques.

KEYWORDS:

1.      Fault ride through

2.      Grid disturbances

3.      Positive synchronous frame

4.      Permanent magnet synchronous generator

5.      Wind-driven generator

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1 PMSG based grid integrated WG.

 EXPECTED SIMULATION RESULTS:

Fig.2 Behavior of PMSG based WG during step change in wind speed (a) wind speed profile, m/s; (b) rotor speed, rad/s; (c) dc-link voltage, V; (d) grid active power, W; (f) grid current, A.

Fig.3 Performance evaluation of proposed controller for the voltage profile of IEGC during symmetrical fault: (a) grid phase voltage, V; (b) MSC active power reference and grid power, W; (c) rotor speed, rad/s; (d) electromagnetic torque, N-m; (e) dc-link voltage, V; (f) grid current, A.

Fig.4 Performance of controllers (I, II and proposed controller) during Type – F fault of 50% voltage sag with -12.5o phase-angle jump (a) dc-link voltage, V; (b) grid active power, W; (c) grid current, A. (d) grid current loci in stationary reference frame during fault period

Fig.5 Performance of controllers (I, II and proposed controller) under distorted utility (a) grid active power, W; (b) grid current, A (zoomed in view).

CONCLUSION:

A modified active power control and current oscillation cancellation scheme are proposed for the MSC and GSC, respectively to strengthen the FRT compliance of the PMSG based WG. A 1.5 MW system is considered to validate the performance of proposed controller. Reduced active power regulation proportionate to retained grid voltage during fault conditions guarantees the dc-link voltage and GSC peak current are within its operating limits. Unlike dual vector control scheme, the GSC is implemented in PSF with oscillation cancellation terms and positive sequence grid angular frequency to suppress the oscillation in system parameters and to obtain symmetrical sinusoidal grid current. The control scheme is validated for various types of fault and distorted grid conditions. The reduced percentage of oscillation in the system parameters as recorded in Table I confirms the efficacy of the proposed method when compared with the controllers (I) and (II). As a future work, the proposed control scheme can be deployed to address weak grid condition with an improvised design.

REFERENCES:

[1] H. Polinder, F. F. A. van der Pijl, G. -J. de Vilder, and P. J. Tavner, “Comparison of Direct-drive and Geared Generator Concepts for Wind Turbines,” IEEE Trans. Energy Convers., vol. 21, no. 3, pp. 725–733, Sep. 2006.

[2] P. Li, Y. -D. Song, D. -Y. Li, W. -C. Cai, and K. Zhang. “Control and Monitoring for Grid-Friendly Wind Turbines: Research Overview and Suggested Approach,” IEEE Trans. Power Electron., vol. 30, no. 4, pp. 1979-1986, Apr. 2015.

[3] M. Chinchilla, S. Arnaltes, and J. Burgos, “Control of Permanent-Magnet Generators Applied to Variable-Speed Wind-Energy Systems Connected to the Grid,” IEEE Trans. Energy Convers., vol. 21, no. 1, pp. 130–135, Mar.2006.

[4] J. F. Conroy and R. Watson, “Low-Voltage Ride-Through of a Full Converter Wind Turbine with Permanent Magnet Generator,” IET Renew. Power. Gener., vol. 1, no. 3, pp. 182–189, Sep. 2007.

[5] A. D. Hansen, and G. Michalke, “Multi-pole Permanent Magnet Synchronous Generator Wind Turbines Grid Support Capability in Uninterrupted Operation during Grid Faults,” IET Renew. Renew. Power Gener., vol. 3, no. 3, pp. 333–348, Nov. 2009.

Wind Speed And Rotor Position Sensorless Control For Direct-Drive PMG Wind Turbines

 ABSTRACT:

Wind turbine generators (WTGs) are usually equipped with mechanical sensors to measure wind speed and rotor position for system control, monitoring, and protection.The use of mechanical sensors increases the cost and hardware complexity and reduces the reliability of the WTG system. This paper proposes a wind speed and rotor position sensorless control for wind turbines directly driving permanent magnetic generators (PMGs). A sliding mode observer is designed to estimate the rotor position of the PMG, which is then used to calculate the shaft rotating speed. Based on the measured output electrical power and estimated rotor speed of the PMG, the mechanical power of the turbine is estimated by taking account into the power losses of the WTG system. A back propagation artificial neural network (BPANN) is then designed to estimate the wind speed in real time by using the estimated turbine shaft speed and mechanical power. The estimated wind speed is used to determine the optimal shaft speed or power reference for the PMG control system. Finally, a sensorless control is developed for the PMG wind turbines to continuously generate the maximum electrical power without using any wind speed or rotor position sensors. The validity of the proposed estimation and control algorithms are shown by simulation studies on a 3- kW PMG wind turbine and are further demonstrated by experimental results on a 300-W practical PMG wind turbine.

KEYWORDS:

1.      Artificial neural network (ANN)

2.      Direct-drive PMG wind turbine

3.      Sensorless control

4.      Sliding mode observer

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

                 

Fig. 1. Configuration of a direct-drive PMG wind turbine connected to a

power grid.

 EXPECTED SIMULATION RESULTS:

Fig. 2. Rotor position estimation results.

Fig. 3. Shaft speed estimation results.

Fig. 4. Shaft mechanical power estimation results.

Fig. 5. Wind speed estimation results.

Fig. 6. Shaft speed tracking results.

Fig. 7. Actual and optimal tip speed ratios.

.

CONCLUSION:

This paper has proposed a novel mechanical sensorless control algorithm for maximum wind power generation using direct-drive PMG wind turbines. The values of wind speed, rotor position, and turbine shaft speed have been estimated from the measured stator voltages and currents of the PMG in real time. These estimated variables were then used for optimal control of the power electronic converters and the PMG. Therefore, the commonly used mechanical sensors in WTG systems, i.e., the wind speed sensors and rotor position sensors, are not needed. The effectiveness of the proposed estimation methods and sensorless control algorithm have been demonstrated by simulation results of a 3-kW PMG wind turbine. Experimental studies have been carried out on a 300-W practical PMG wind turbine system to further validate the proposed speed estimation algorithms.

REFERENCES:

[1] J. Ribrant and L. M. Bertling, “Survey of failures in wind power systems with focus on Swedish wind power plants during 1997-2005,” IEEE Trans. Energy Conversion, vol. 22, no. 1, pp. 167-173, Mar. 2007.

[2] W. Qiao, W. Zhou, J. M. Aller, and R. G. Harley, “Wind speed estimation based sensorless output maximization control for a wind turbine driving a DFIG,” IEEE Trans. Power Electronics, vol. 23, no. 3, pp. 1156-1169, May 2008.

[3] B. Boukhezzar and H. Siguerdidjane, “Nonlinear control of variable speed wind turbines without wind speed measurement,” in Proc. 44^th IEEE Conference on Decision and Control, Seville, Spain, Dec. 12-15, 2005, pp. 3456-3461.

[4] T. Tanaka and T. Toumiya, “Output control by Hill-Climbing method for a small wind power generating system,” Renewable Energy, vol. 12, no. 4, pp. 387-400, 1997.

[5] M. G. Simoes, B. K. Bose, and R. J. Spiegel, “Fuzzy logic based intelligent control of a variable speed cage machine wind generation system,” IEEE Trans. Power Electronics, vol. 12, no. 1, pp. 87-95, Jul./Aug. 1997.

A Novel Design of PI Current Controller for PMSG-based Wind Turbine Considering Transient Performance Specifications and Control Saturation

 ABSTRACT:

This paper presents a novel design process of decoupled PI current controller for permanent magnet synchronous generator (PMSG)-based wind turbines feeding a grid-tied inverter through back-to-back converter. Specifically, the design methodology consists of combining disturbance observer-based control (DOBC) with feedback linearization (FBL) technique to ensure nominal transient performance recovery under model uncertainty. By simplifying the DOBC under the feedback linearizing control, it is shown that the composite controller reduces to a decoupled PI current controller plus an additional term that has the main role of recovering the nominal transient performance of the feedback linearization, especially under step changes in the reference. Additionally, an anti windup compensator arises naturally into the controller when considering the control input saturation to design the  DOBC. This permits to remove the effect of the saturation blocks required to limit the control input. The proposed control scheme is implemented and validated through experimentation conducted on 22-pole, 5 kW PMSG. The results revealed that the proposed technique can successfully achieve nominal performance recovery under model uncertainty as well as improved transient performances under control saturation.

KEYWORDS:

1.      Anti-windup scheme

2.      Disturbance observer

3.      Nominal performance recovery

4.      Permanent magnet synchronous generator (PMSG)

5.      PI controller

6.      Renewable energy

7.      Wind energy conversion system

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Configuration of a direct-drive PMSG-based WECS connected

to the host grid.

 EXPECTED SIMULATION RESULTS:

Fig. 2. System’s response under the composite controller consisting of the feedback controller (13) and the PI-DO (34)–(37). The controller was tested experimentally using the block diagram of Fig. 3. Specifically, the PI-DO (34)–(37) was evaluated with and without the consideration of the reference jump .

Fig. 3. System’s response under the composite controller consisting of the feedback controller (13) and the DOBC (25). The controller was tested experimentally using the block diagram depicted in Fig. 2.

Fig. 4. System’s response under a conventional PI current controller [17].

Fig. 5. Performance evaluation of the proposed PI-DO under model uncertainty.

Fig. 6. Experimental results: Performance testing of the proposed PI current controller under MPPT algorithm, with id (2 A/div), iq (4 A/div), ia (10 A/div), ws (5 [m/s]/div), iga (6 A/div), r (50 [rpm/min]/div), and time (400 ms/div)

CONCLUSION:

This paper has presented a novel design of decoupled PI controller to enhance the transient performance for the current control of PMSG-based wind turbine. The proposed controller technique was established by combining a DOBC with feedback linearizing control law. It turns out that the composite controller has a decoupled PI-like structure plus two additional parts. The first part is basically an anti-windup compensator, while the second part uses the reference jump information to cancels out the effect of the sudden step changes in the power demand on the transient response. This modification of the decoupled PI controller permits to guarantee zero steady-state error without sacrificing the nominal transient performance specified by the state feedback controller. This salient feature cannot be achieved under the existing decoupled PI controller, particularly when the model parameters are not accurate. Experimental tests have been performed, and the results support the use of the reference jump information to improve the transient performance under the decoupled PI controller. Therefore, the proposed approach provides practitioners with an alternate method in designing a robust decoupled PI current controller for PMSG-based wind energy conversion system.

REFERENCES:

[1] N. A. Orlando, M. Liserre, R. A. Mastromauro, and A. Dell’Aquila, “A survey of control issues in PMSG-based small wind-turbine systems,” IEEE Trans. Ind. Inform., vol. 9, no. 3, pp. 1211–1221, Aug 2013.

[2] Y. Wang, J. Meng, X. Zhang, and L. Xu, “Control of PMSG-based wind turbines for system inertial response and power oscillation damping,” IEEE Trans. on Sustainable Energy, vol. 6, no. 2, pp. 565–574, April 2015.

[3] S. Benelghali, M. E. H. Benbouzid, J. F. Charpentier, T. Ahmed-Ali, and I. Munteanu, “Experimental validation of a marine current turbine simulator: Application to a permanent magnet synchronous generator based system second-order sliding mode control,” IEEE Trans. Ind. Electron, vol. 58, no. 1, pp. 118–126, Jan 2011.

[4] C. Wei, Z. Zhang, W. Qiao, and L. Qu, “An adaptive network-based reinforcement learning method for MPPT control of PMSG wind energy conversion systems,” IEEE Trans. Power Electron., vol. 31, no. 11, pp. 7837–7848, Nov 2016.

[5] H. M. Yassin, H. H. Hanafy, and M. M. Hallouda, “Enhancement low-voltage ride through capability of permanent magnet synchronous generator-based wind turbines using interval type-2 fuzzy control,” IET Renew. Power Gen., vol. 10, no. 3, pp. 339–348, 2016.