Control of a Small Wind Turbine in the High Wind Speed Region

ABSTRACT:

This paper proposes another delicate slowing down control methodology for network associated little wind turbines working in the high and high wind speed conditions. The proposed strategy is driven by the evaluated flow/torque points of confinement of the electrical machine as well as the power converter, rather than the appraised intensity of the associated load, which is the restricting variable in different techniques. The created technique furthermore manages the issue of framework startup keeping the generator from quickening to a wild working point under a high wind speed circumstance. This is practiced utilizing just voltage and current sensors, not being required direct estimations of the breeze speed nor the generator speed. The proposed strategy is connected to a little wind turbine framework comprising of a perpetual magnet synchronous generator and a basic power converter topology. Reproduction and test results are incorporated to exhibit the execution of the proposed technique. The paper additionally demonstrates the impediments of utilizing the stator back-emf to gauge the rotor speed in changeless magnet synchronous generators associated with a rectifier, because of noteworthy d-pivot current at high load.

 CIRCUIT DIAGRAM:

Fig. 1. Schematic representation of the wind energy generation system: a) Wind turbine, generator and power converter; b) Block diagram of the boost converter control system; c) Block diagram of the H-bridge converter control system.

EXPECTED SIMULATION RESULTS:

 

Fig. 2. Simulation result showing the behavior of the proposed method under increasing wind conditions (10 m/s, 17 m/s from 10 s, and 33 m/s from 13s): a) rectifier voltage command (v_ r ), rectifier voltage (vr) and minimum rectifier voltage command (v_ r min); b) boost current (ib), filtered boost current (~i b), current limit (ilimit) and MPPT current target (imppt); c) turbine torque (Tt) and generator torque (Tg); d) mechanical rotor speed (!rm).

 Fig. 3. Simulation result showing the behavior of the proposed method under decreasing wind conditions (30 m/s, 21 m/s from 4.5 s, and 8.5 m/s from 7s): a) rectifier voltage command (v_ r ), rectifier voltage (vr) and minimum rectifier voltage command (v_ r min); b) boost current (ib), filtered boost current (~I b), current limit (ilimit) and MPPT current target (imppt); c) turbine torque (Tt) and generator torque (Tg); d) mechanical rotor speed (!rm).

Fig. 4. Experimental results showing the behavior of the propose method under increasing wind conditions (10 m/s, 17 m/s from 10 s, and 33 m/s from 13 s): a) rectifier voltage command (v_ r ), rectifier voltage (vr) and minimum rectifier voltage command (vr min); b) boost current (ib), filtered boost current (~I b), current limit (ilimit) and MPPT current target (imppt); c) mechanical rotor speed (!rm).

 Fig. 5. Experimental results showing the behavior of the propose method under decreasing wind conditions (30 m/s, 21 m/s from 4.5 s, and 8.5 m/s from 9 s): a) rectifier voltage command (v_ r ), rectifier voltage (vr) and minimum rectifier voltage command (vr min); b) boost current (ib),filtered boost current (~I b), current limit (ilimit) and MPPT current target (imppt); c) mechanical rotor speed (!rm).

CONCLUSION:

The activity of little wind turbines for local or private venture use is driven by two variables: cost and practically unsupervised task. Extraordinarily essential is the turbine activity and insurance under high wind speeds, where the turbine torque can surpass the appraised torque of the generator. This paper proposes a delicate slow down strategy to diminish the turbine torque if a high wind speed emerges and, as a special element, the technique can early distinguish a high wind condition at startup keeping the turbine/generator running at low rotor speed maintaining a strategic distance from progressive begin and stop cycles. The proposed strategy utilizes just voltage and current sensors commonly found in little turbines making it a reasonable arrangement. Both reenactment and trial results show the legitimacy of the proposed ideas. This paper additionally demonstrates that generally utilized machine and rectifier models accepting solidarity control factor don’t give precise estimations of the generator speed in stacked conditions, regardless of whether the resistive and inductive voltage drop are decoupled, because of the noteworthy flow of d-pivot current if a PMSG is utilized. This paper proposes utilizing a pre-dispatched look-into table whose inputs are both the rectifier yield voltage and the lift current.

A Unified Nonlinear Controller Design for On-grid/Off-grid Wind Energy Battery-Storage System

ABSTRACT:

The objective of this paper is to explore the utilization of nonlinear control strategy to a multi-input multi yield (MIMO) nonlinear model of a breeze vitality battery stockpiling framework utilizing a changeless magnet synchronous generator (PMSG). The test is that the framework ought to work in both matrix associated and independent modes while guaranteeing a consistent progress between the two modes and an effective power circulation between the heap, the battery and the network. Our methodology is unique in relation to the regular techniques found in writing, which utilize an alternate controller for every one of the modes. Rather, in this work, a solitary bound unified nonlinear controller is proposed. The proposed unified nonlinear control framework is assessed in recreation. The outcomes demonstrated that the proposed control conspire gives high unique reactions because of network control blackout and load variety just as zero relentless state mistake.

 

BLOCK DIAGRAM:

 

Fig. 1. WECS based permanent magnet synchronous generator.

 EXPECTED SIMULATION RESULTS:

Fig. 2. Optimum Rotor Speed and Output Power.

Fig. 3. Voltage and current of the load.

Fig. 4. dc-link voltage.

Fig. 5. Wind Turbine Output Power (MW).

Fig. 6. Load Power (MW).

Fig. 7. Charge/discharge of Battery (%).

Fig. 8. Grid Power (MW).

CONCLUSION:

This paper has proposed a nonlinear MIMO controller dependent on the criticism linearization hypothesis to direct the heap voltage in both matrix associated and remain solitary mode while guaranteeing a consistent change between the two modes and an effective power dispersion between the heap, the battery and the network. Our methodology is not quite the same as the regular strategies found in writing, which utilize an alternate controller, PID based, for every method of activity. Rather, in this work, a solitary bound together nonlinear controller is proposed. The execution of the proposed controller has been tried with various breeze speeds just as in the two methods of activity with dynamic load. The recreation results demonstrate that applying nonlinear input linearization based control procedure gives a decent control execution. This execution is portrayed by quick and smooth transient reaction just as great consistent state soundness and reference following quality, even with variable breeze speed and dynamic load activity. Be that as it may, this examination expect that the framework parameters are settled. A future work will be to test the framework when parameters are obscure utilizing versatile control structure hypothesis.

Grid Connected Wind- Photovoltaic hybrid System

ABSTRACT

 This paper presents a modeling and control strategies of a grid connected Wind-Photo voltaic hybrid system. This proposed system consists of two renewable energy sources in order to increase the system efficiency. The Maximum Power Point Tracking (MP PT) algorithm is applied to the P V system and the wind system to obtain the maximum power for any given external weather conditions. The Field Oriented Control (F O C) controls the generator side converter, moreover this approach is used to control independently the flux and the torque by applying the d- and q-components of the current motor. The Voltage Oriented Control (V O C) strategy controls the utility grid side converter which is adopted to adjust the DC-link at the desired voltage. The simulation results using mat lab software environment prove the good performance of these used techniques so as to generate sinusoidal current wave forms. This current synchronizes with the grid voltage, Moreover, the DC bus voltage is perfectly constant because only the active power is injected into the grid. Simulations are carried out to validate the effectiveness of the proposed system methods.

 

BLOCK DIAGRAM

 

Fig. l.The proposed P V -wind hybrid system

 EXPECTED SIMULATION RESULTS

Fig. 2 Solar i r radiance changes

Fig. 3 The variation of PY arrays current

Fig. 4 The P Y arrays voltage

Fig. 5 The P Y arrays power and reference

Fig. 6 Duty cycle

Fig. 7 Wind speed profile

Fig. 8 Electrical angular speed of the SC I G and its reference

Fig. 9 The active power injected into the grid

Fig. 10 The Reactive power injected into the grid

Fig. 11 The wave forms of the current

Fig. 12 The three phase current and voltage wave forms

Fig. 13. DC link voltage.

CONCLUSION

This paper investigated the Wind-Photo voltaic hybrid system control which included an MP PT method. Different solar irradiation and wind speed environments has been simulated in order to maximize the output power of the proposed system . Two control techniques  improved the hybrid system usefulness. The Field Oriented Control (F O C) controlled the controlled rectifier connected to the squirrel-cage induction generator (SCI G) to reach the optimal rotational speed. The Voltage Oriented Control (V O C) method controlled the grid-side invert er in order to keep the dc-link voltage at the desired value. Mat lab / Sim u link software implemented the hybrid system simulation and its performances proved when the solar i r radiance change or the wind speed occurs.

 

Modeling, Implementation and Performance Analysis of a Grid-Connected Photovoltaic/Wind Hybrid Power System

ABSTRACT:

This paper investigates dynamic modeling, design and control strategy of a grid-connected photovoltaic (PV)/wind hybrid power system. The hybrid power system consists of PV station and wind farm that are integrated through main AC-bus to enhance the system performance. The Maximum Power Point Tracking (MPPT) technique is applied to both PV station and wind farm to extract the maximum power from hybrid power system during variation of the environmental conditions. The modeling and simulation of hybrid power system have been implemented using Matlab/Simulink software. The effectiveness of the MPPT technique and control strategy for the hybrid power system is evaluated during different environmental conditions such as the variations of solar irradiance and wind speed. The simulation results prove the effectiveness of the MPPT technique in extraction the maximum power from hybrid power system during variation of the environmental conditions. Moreover, the hybrid power system operates at unity power factor since the injected current to the electrical grid is in phase with the grid voltage. In addition, the control strategy successfully maintains the grid voltage constant irrespective of the variations of environmental conditions and the injected power from the hybrid power system.

KEYWORDS:

  1. PV
  2. Wind
  3. Hybrid system
  4. Wind turbine
  5. DFIG
  6. MPPT control

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. The system configuration of PV/wind hybrid power system.

 EXPECTED SIMULATION RESULTS:

(a) Solar Irradiance.

(b) PV array voltage.

(c) PV array current.

(d) A derivative of power with respect to voltage (dPpv/dVpv).

Fig. 2. Performance of PV array during the variation of solar irradiance.

(a) PV DC-link Voltage.

(b) d-q axis components of injected current from PV station.

(c) Injected active and reactive power from PV station.

(d) Grid voltage and injected current from PV station.

(e) The power factor of the inverter.

(f) Injected current from PV station.

Fig. 3. Performance of PV station during variation of the solar irradiance.

(a) Wind speed profile.

(b) The mechanical torque of wind turbine.

(c) The DC-bus voltage of DFIG.

(d) Injected active and reactive power from the wind farm.

(e) The power factor of the wind farm.

(f) Injected current from the wind farm.

Fig. 4. Performance of wind farm during variation of the wind speed.

(a) Power flow between PV station, wind farm, and hybrid power system.

(b) Injected active and reactive power from the hybrid system.

(c) PCC-bus voltage.

Fig. 5. Performance of hybrid power system at PCC-bus.

 CONCLUSION:

In this paper, a detailed dynamic modeling, design and control strategy of a grid-connected PV/wind hybrid power system has been successfully investigated. The hybrid power system consists of PV station of 1MW rating and a wind farm of 9 MW rating that are integrated through main AC-bus to inject the generated power and enhance the system performance. The incremental conductance MPPT technique is applied for the PV station to extract the maximum power during variation of the solar irradiance. On the other hand, modified MPPT technique based on mechanical power measurement is implemented to capture the maximum power from wind farm during variation of the wind speed. The effectiveness of the MPPT techniques and control strategy for the hybrid power system is evaluated during different environmental conditions such as the variations of solar irradiance and wind speed. The simulation results have proven the validity of the MPPT techniques in extraction the maximum power from hybrid power system during variation of the environmental conditions. Moreover, the hybrid power system successfully operates at unity power factor since the injected reactive power from hybrid power system is equal to zero. Furthermore, the control strategy successfully maintains the grid voltage constant regardless of the variations of environmental conditions and the injected power from the hybrid power system.

REFERENCES:

[1] H. Laabidi and A. Mami, “Grid connected Wind-Photovoltaic hybrid system,” in 2015 5th International Youth Conference on Energy (IYCE), pp. 1-8,2015.

[2] A. B. Oskouei, M. R. Banaei, and M. Sabahi, “Hybrid PV/wind system with quinary asymmetric inverter without increasing DC-link number,” Ain Shams Engineering Journal, vol. 7, pp. 579-592, 2016.

[3] R. Benadli and A. Sellami, “Sliding mode control of a photovoltaic-wind hybrid system,” in 2014 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM), pp. 1-8, 2014.

[4] A. Parida and D. Chatterjee, “Cogeneration topology for wind energy conversion system using doubly-fed induction generator,” IET Power Electronics, vol. 9, pp. 1406-1415, 2016.

[5] B. Singh, S. K. Aggarwal, and T. C. Kandpal, “Performance of wind energy conversion system using a doubly fed induction generator for maximum power point tracking,” in Industry Applications Society Annual Meeting (IAS), 2010 IEEE, 2010, pp. 1-7.

 

Fault Ride-Through of a DFIG Wind Turbine Using a Dynamic Voltage Restorer During Symmetrical and Asymmetrical Grid Faults

ABSTRACT:

 The application of a dynamic voltage restorer (DVR) connected to awind-turbine-driven doubly fed induction generator (DFIG) is investigated. The setup allows the wind turbine system an uninterruptible fault ride-through of voltage dips. The DVR can compensate the faulty line voltage, while the DFIG wind turbine can continue its nominal operation as demanded in actual grid codes. Simulation results for a 2 MW wind turbine and measurement results on a 22 kW laboratory setup are presented, especially for asymmetrical grid faults. They show the effectiveness of the DVR in comparison to the low-voltage ride-through of the DFIG using a crowbar that does not allow continuous reactive power production.

 KEYWORDS:

  1. Doubly fed induction generator (DFIG)
  2. Dynamic voltage restorer (DVR)
  3. Fault ride-through and wind energy

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fault Ride-Through of a DFIG

Fig. 1. Schematic diagram of DFIG wind turbine system with DVR.

 EXPECTED SIMULATION RESULTS:

 

Fig. 2. Simulatin of DFIG performance with crowbar protection during 37 % two-phase voltage dip. (a) Line voltage. (b) DVR voltage. (c) Stator voltage. (d) Stator current. (e) RSC current. (f) Crowbar current. (g) Mechanical speed. (h) Active and reactive stator power. (i) Active and reactive DVR power.

Fig. 3. Simulation of DFIG performance with DVR protection during 37 % two-phase voltage dip. (a) Line voltage. (b) DVR voltage. (c) Stator voltage. (d) Stator current. (e) RSC current. (f) Crowbar current. (g) Mechanical speed. (h) Active and reactive stator power. (i) Active and reactive DVR power.

Fig. 4. Measurement results for DFIG with crowbar protection: (a) stator

voltages, (b) stator currents, and (c) rotor currents.

Fig. 5. Measurement results for DFIG with DVR protection: (a) line voltages, (b) DVR voltages, (c) stator voltages, (d) stator currents, and (e) rotor currents.

CONCLUSION:

The application of a DVR connected to a wind-turbine-driven DFIG to allow uninterruptible fault ride-through of grid voltage faults is investigated. The DVR can compensate the faulty line voltage, while the DFIG wind turbine can continue its nominal operation and fulfill any grid code requirement without the need for additional protection methods. The DVR can be used to protect already installed wind turbines that do not provide sufficient fault ride-through behavior or to protect any distributed load in a microgrid. Simulation results for a 2 MW wind turbine under an asymmetrical two-phase grid fault show the effectiveness of the proposed technique in comparison to the low-voltage ridethrough of the DFIG using a crowbar where continuous reactive power production is problematic. Measurement results under transient grid voltage dips on a 22 kW laboratory setup are presented to verify the results.

REFERENCES:

[1] M. Tsili and S. Papathanassiou, “A review of grid code technical requirements for wind farms,” Renewable Power Generat., IET, vol. 3, no. 3, pp. 308–332, Sep. 2009.

[2] R. Pena, J. Clare, and G. Asher, “Doubly fed induction generator using back-to-back pwm converters and its application to variable-speed windenergy generation,” Electr. Power Appl., IEE Proc., vol. 143, no. 3, pp. 231–241, May 1996.

[3] S.Muller,M.Deicke, andR.DeDoncker, “Doubly fed induction generator systems for wind turbines,” IEEE Ind. Appl.Mag., vol. 8, no. 3, pp. 26–33, May/Jun. 2002.

[4] J. Lopez, E. Gubia, P. Sanchis, X. Roboam, and L. Marroyo, “Wind turbines based on doubly fed induction generator under asymmetrical voltage dips,” IEEE Trans. Energy Convers., vol. 23, no. 1, pp. 321–330, Mar. 2008.

[5] M. Mohseni, S. Islam, and M. Masoum, “Impacts of symmetrical and asymmetrical voltage sags on dfig-based wind turbines considering phaseangle jump, voltage recovery, and sag parameters,” IEEE Trans. Power Electron., to be published.