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Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system.

M F Roslan1, Ali Q Al-Shetwi2,3, M A Hannan1

  • 1Department of Electrical Power Engineering, Universiti Tenaga Nasional, Kajang, Selangor, Malaysia.

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This study optimizes a proportional-integral (PI) controller for grid-connected photovoltaic (PV) systems using particle swarm optimization (PSO). The enhanced control strategy significantly improves power quality by reducing voltage overshoot and transient response times.

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Area of Science:

  • Electrical Engineering
  • Renewable Energy Systems
  • Control Systems

Background:

  • Grid-connected photovoltaic (PV) systems face challenges with voltage overshoot, transient response, and steady-state errors, impacting power quality and system stability.
  • These issues can lead to power quality degradation and potential damage within the overall power system infrastructure.

Purpose of the Study:

  • To enhance the power quality of a three-phase grid-connected PV inverter system.
  • To optimize the proportional-integral (PI) controller parameters for improved system performance.
  • To reduce DC link voltage fluctuations, harmonics, and stabilize output current, voltage, frequency, and power flow.

Main Methods:

  • Implementation of a control strategy for a three-phase grid-connected PV system, including a PV panel, boost converter, DC link, inverter, and RL filter.
  • Utilizing the particle swarm optimization (PSO) technique to tune PI controller parameters by minimizing voltage and current controller errors.
  • System modeling and control strategy implementation using MATLAB/Simulink with the Simscape-Power system toolbox.

Main Results:

  • The proposed PSO-tuned PI controller significantly reduced total harmonic distortion (THD) in grid voltage (0.29%) and current (2.72%).
  • Achieved a fast transient response time of 0.1853 seconds, with an 11.1% reduction in voltage overshoot compared to conventional systems.
  • Demonstrated a 32.6% decrease in the time to reach the equilibrium state, highlighting improved stability.

Conclusions:

  • The PSO-based optimization of the PI controller effectively enhances the power quality of grid-connected PV systems.
  • The optimized control strategy leads to reduced voltage fluctuations, lower harmonic content, and stabilized system parameters.
  • This improved power quality facilitates more efficient and seamless integration of PV systems into the utility grid.