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A NOVEL MAXIMUM POWER TRACKING CONTROLLER FOR A STAND-ALONE PHOTOVOLTAIC DC MOTOR DRIVE

A NOVEL MAXIMUM POWER TRACKING CONTROLLER FOR A STAND-ALONE PHOTOVOLTAIC DC MOTOR DRIVE. A.M. Sharaf, SM-IEEE Department of Electrical and Computer Engineering University of New Brunswick. PRESENTATION OUTLINE. Introduction Green Power GP Solar System Model

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A NOVEL MAXIMUM POWER TRACKING CONTROLLER FOR A STAND-ALONE PHOTOVOLTAIC DC MOTOR DRIVE

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  1. A NOVEL MAXIMUM POWER TRACKING CONTROLLERFOR A STAND-ALONE PHOTOVOLTAIC DC MOTOR DRIVE A.M. Sharaf, SM-IEEE Department of Electrical and Computer Engineering University of New Brunswick

  2. PRESENTATION OUTLINE • Introduction • Green Power GP Solar System Model • Novel Dynamic Error Driven Controller • Digital Simulation Results • Conclusions • Future Green Power Energy-Farm

  3. Introduction The advantages of PV solar energy: • Clean and green energy source that can reduce green house gases • Highly reliable and needs minimal maintenance • Costs little to build and operate ($2-3/Wpeak) • Almost has no environmental polluting impact • Modular and flexible in terms of size, ratings and applications

  4. Maximum Power Point Tracking (MPPT) • The photovoltaic system displays an inherently nonlinear current-voltage (I-V) relationship, requiring an online search and identification of the optimal maximum power operating point. • MPPT controller/interface is a power electronic DC/DC converter or DC/AC inverter system inserted between the PV array and its electric load to achieve the optimum characteristic matching • PV array is able to deliver maximum available solar power that is also necessary to maximize the photovoltaic energy utilization in stand-alone energy utilization systems (water pumping, ventilation)

  5. I-V and P-V characteristics of a typical PV array at a fixed ambient temperature and solar irradiation condition

  6. The performance of any stand-alone PV system depends on: • Electric load operating conditions/Sudden-Excursions/ Load Switching • Ambient/junction temperature (Tx) • Solar Irradiation variations (Sx)

  7. System Model Description Key System components: • PV array module model • Power conditioning input-filter: ♦ Blocking Diode ♦ Input Inductor (Rf & Lf) • Energy-Storage Capacitor (C1) • Four-Quadrant PWM converter feeding the PMDC (Permanent Magnet Direct Current) motor (1-15kW size)

  8. Photovoltaic powered Four-Quadrant PWM converter PMDC motor drive system

  9. Novel Dynamic Error Driven Self Adjusting Controller (SAC) SAC has Three -Regulating Loops: • The main -motor reference speed (ωm-reference) trajectory tracking loop • The first supplementary motor current (Im) limiting loop • The second supplementary maximum photovoltaic power (Pg) tracking loop

  10. Dynamic tri-loop self adjusting control (SAC) system

  11. The global error signal (et) comprises 3-dimensional excursion vectors (ew, ei, ep) • The nonlinear control -modulation ΔVc is • β is the specified squashing order (2~3) • │Re│ is the magnitude of the hyper-plane error excursion vector at time instant k

  12. The loop weighting factors (γw, γI and γp) and the parameters k0 and β are assigned to minimize the time-weighted excursion index J0 where • N= T0/Tsample • T0: Largest mechanical time constant (10s) • Tsample: Sampling time (0.2ms) • t(k)=k·Tsample: Time at step k in seconds

  13. Digital Simulation Results • Photovoltaic powered Four-Quadrant PWM converter PMDC motor drive system model using the MATLAB/Simulink/SimPowerSystems software

  14. Variation of ambient temperature (Tx) Variation of solar irradiation (Sx) Test Variations of ambient temperature and solar irradiation

  15. Ig vs. time Pg vs. time Vg vs. time Vg vs. Ig For trapezoidal reference speed trajectory

  16. Pg vs. Ig & Vg ωref & ωm vs. time Iam vs. time ωm vs. Te For trapezoidal reference speed trajectory(Continue)

  17. Ig vs. time Pg vs. time Vg vs. time Vg vs. Ig For sinusoidal reference speed trajectory

  18. Pg vs. Ig & Vg ωref & ωm vs. time Iam vs. time ωm vs. Te For sinusoidal reference speed trajectory(Continue)

  19. Matlab/Simulink digital simulation results validate the tri-loop dynamic error driven Self-Adjusting Controller (SAC) to ensure: • Good reference speed trajectory tracking with a small overshoot/undershoot and minimum steady state error • The motor inrush current Im is kept to a specified limited value • Maximum PV solar power/energy tracking near optimal MPPT-knee point operation can be also achieved

  20. Conclusions • The proposed dynamic error driven controller requires only the PV array output voltage and current signals and the DC motor speed and current signals that can be easily measured. • The low cost stand-alone photovoltaic renewable energy scheme is suitable for village electricity application in the range of (150 watts to 15000 watts), mostly for water pumping and irrigation use in arid developing countries.

  21. Future Work • Other Low-Cost Standalone or Grid connected Dispersed/distributed PV-DC, PV-AC and Hybrid PV/Wind /Fuel Cell/Small- Hydro/Micro-gas turbines / Bio-diesel/…Renewable/Sustainable Green Power GP-energy utilization schemes • New VSC-Facts based Converter Schemes and control strategies for Wind and Hybrid Energy-Farms

  22. Future Work (Continue)Novel Variable Structure Flexi-Dynamic Error DrivenSliding Mode Controller (SMC) Three regulating loops: • The motor reference speed (ωm-reference) trajectory tracking loop • The first supplementary motor current (Im) limiting loop • The second supplementary maximum photovoltaic power (Pg) tracking loop

  23. Dynamic tri-loop error-driven Sliding Mode Control (SMC) system

  24. The loop weighting factors (γw,γi and γp) and the parameters C0 and C1 are assigned to minimize the time-weighted excursion index J0 where • N= T0/Tsample • T0: Largest mechanical time constant (10s) • Tsample: Sampling time (0.2ms)

  25. Thank You! & Questions?

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