Published on Feb 15, 2016
Renewable energy sources are becoming a viable substitute for conventional energy sources due to increases in world's energy demand and scarce resources.
Solar pump operated with AC drive offer better choice in terms of size, ruggedness, efficiency and maintainability. In this work, dc power from solar panel is boosted and fed to an inverter which gives ac output. Inverter drives the motor coupled to the water pump.
To get the maximum power available at any instant an MPPT controller is used to control the converter. Of different types of MPPT algorithms artificial intelligence (AI) techniques are popular. Artificial neural networks (ANNs) & fuzzy logic (FL) two different types of AI techniques that are used to design the MPPT controller for PV system.
In this proposed work, depending on solar radiation and temperature, the MPPT controller gives optimized duty cycle.
Neural network and fuzzy logic are two MPPT controllers, simulated to give optimum duty cycle. These MPPT controllers are compared based on the power obtained from the boost converter. Simulation results are also presented.