PSO-optimized electronic load controller with intelligent energy recovery for self-excited induction generator based...

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Systems

Background:

• Off-grid micro-hydro systems require robust Electronic Load Controllers (ELCs) for stable power generation.
• Conventional ELCs often dissipate excess energy as heat, leading to inefficiency.
• Self-Excited Induction Generators (SEIGs) are common in micro-hydro but need effective load management.

Purpose of the Study:

• To develop and validate a novel Particle Swarm Optimisation (PSO)-based ELC for SEIG systems.
• To enable intelligent energy recovery through adaptive water pumping, minimizing energy waste.
• To simultaneously optimize voltage regulation, frequency stability, and harmonic reduction.

Main Methods:

• Multi-objective PSO algorithms were employed to optimize PI controller gains, PWM switching parameters, and power distribution.
• A comprehensive fitness function integrated voltage error, frequency deviation, total harmonic distortion (THD), and energy recovery efficiency.
• Experimental validation was performed on a 2.2 kW laboratory prototype.

Main Results:

• Achieved superior voltage regulation (±0.5%) and frequency stability (±0.1 Hz) compared to conventional methods.
• Demonstrated high energy recovery efficiency (92.1%) via intelligent water pumping, eliminating resistive energy waste.
• Reduced total harmonic distortion to 5.8%, ensuring IEEE 519 compliance, with rapid PSO convergence (15.2 iterations).

Conclusions:

• The proposed PSO-based intelligent ELC offers a sustainable and efficient solution for off-grid micro-hydro applications.
• Significant economic benefits include annual savings of $1567 and a 2.1-year payback period.
• The system establishes a new paradigm for micro-hydro energy management with high availability and productive water storage.