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Tuesday, 13 July 2021

LMMN Based Adaptive Control for Power Quality Improvement of Grid Intertie Wind-PV System

ABSTRACT:

  A new topology comprising of wind turbine driven synchronous generator (SG) and solar photovoltaic (PV) array for renewable energy harvesting, is proposed in this work. The stochastic inputs for proposed system, are agitated by the nonlinear time dependent parameters such as variable wind speed and changing solar insolation. The speed variations are absorbed using back to back interfaced power electronic converters (PECs) namely synchronous generator side converter (SGC) and utility grid side converter (UGC) with a common DC link where solar PV array is tied directly. The power injection into the utility grid, is levelled by the optimal utilization of PECs. The SGC uses vector control (VC) for speed control of SG and maintains unity power factor (UPF) at stator terminals. UGC acquires its switching pulses with proper application of least mean mixed norm (LMMN) control technique. The new application of LMMN control scheme is used for harmonics compensation and fundamental load component extraction. The DC link voltage is regulated using proportional integral (PI) controller. A prototype is developed and tested under different conditions of sudden changes in load, wind velocity variations as well as under varying solar PV insolation. The power sharing scheme proves to be effective. The power quality (PQ) issues are also addressed and mitigated effectively. The performance is exhibited for the validation of the proposed system and its control.

KEYWORDS:

1.      Utility Grid

2.      Wind

3.      SG

4.      Solar PV Array

5.      SGC

6.      UGC

7.      LMMN Control

8.      Load Compensation

9.      Power Quality

SOFTWARE: MATLAB/SIMULINK

CONCLUSION:

A three-phase grid intertie wind-PV system with effective load compensation capability, is proposed and its suitability is justified through hardware validation on a developed prototype in the laboratory under various operating conditions such as changing wind velocity, variations in solar insolation and perturbation in nonlinear load. The parallel operation of solar PV array and wind driven SG, allows a possibility of load sharing. The fundamental extraction from the load currents, is successfully done with the application of LMMN adaptive filtering control. The load current fundamental component is extracted, moreover, the disturbances and harmonic content in grid currents are removed in order to improve the power quality at CPI. The aim of improving the voltage profile and reducing the harmonic content at the CPI, is attained successfully by implementing the LMMN adaptive control. The LMMN adaptive control schemes, leads to fast response and less misadjustments. The maximum power is extracted effectively from solar PV array and wind turbine using P&O algorithm. Sensorless VC for speed control of SG, has resulted in low system cost and increased system reliability. Test results obtained under steady state and dynamic conditions, show the acceptability of control techniques. Moreover, the grid currents under the enforced conditions, have their THD below 5% confirming to the IEEE-519 standard.

REFERENCES:

[1] O. A. Lara, N. Jenkins, J. Ekanayake, P. Cartwright and M. Hughes, “Wind energy Generation Modelling and control”, Wiley-IEEE Press, 2009.

[2] V. A. Suryad, S. Doolla and M. Chandorkar, “Microgrids in India: Possibilities and Challenges,” IEEE Electrif. Magazine, vol. 5, no. 2, pp. 47-55, June 2017.

[3] M. Faisal, M. A. Hannan, P. J. Ker, A. Hussain, M. Mansur and F. Blaabjerg, “Review of energy storage system technologies in microgrid applications: Issues and challenges,” IEEE Access, 2018.

[4] M. G. Molina, “Energy storage and power electronics technologies: a strong combination to empower the transformation to the smart grid,” Proc. IEEE, vol. 105, no. 11, pp. 2191-2219, Nov. 2017.

[5] R. Vijayapriya, P. Raja and M. P. Selvan, “A modified active power control scheme for enhanced operation of PMSG based WGS,” IEEE Trans. Sustain. Ener., Early Access.