MPPT Using Particle Swarm Optimization and Artificial Bee Colony Algorithm
Abstract
Solar power plant is a renewable electricity generator that utilizes heat from sunlight. However, because the intensity of light received by the solar cell and the temperature in the solar cell is always changing, the power generated is not optimal. To optimize the output power of the solar cell, a Maxi-mum Power Point Tracking (MPPT) system is needed. Solar cells can be optimized by looking for MPPT and also by using a DC-DC converter. In this study, boost converter is optimized using Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms. The results show that the highest efficiency obtained from boost converter is 78.25%,using duty cycle of 20%. For the overall system testing conducted at 09:00 WIB until 11:10 WIB, the average power obtained without using MPPT is 12.55 W, the average power of MPPT system using boost converter with PSO algorithm is 16.79 W, and average power of MPPT system using boost converter with ABC algorithm is 14.52 W. From the results, it was concluded that the output power of MPPT system using boost converter with PSO algorithm is more optimal than the MPPT system using boost converter with ABC algorithm.
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