| Summary: | 碩士 === 國立成功大學 === 系統及船舶機電工程學系 === 103 === The research evaluates and compares the application of two Multivariate Maximal Power Point Tracking Methods on Distributed Photovoltaic System. These two algorithms are Steepest Descent Method and Particle Swarm Optimization (PSO). Since these types of tracking methods reduce the elements needed in distributed photovoltaic system hardware, the practical application would then reduce the cost of photovoltaic system. The paper will focus on the MPPT experiments of the stimulation systems according to different series-parallel combinations of photovoltaic system.
There are two programs used to simulate systems: Multisim and Labview; in order to simulate transient changes of circuit and then further evaluate the best algorithm and hardware collocations. In addition, through tracking with various series-parallel combinations, the algorithm can achieve certain performance with different configurations.
The experiment is composed of four CSSS-090A photovoltaic panels. Through different series-parallel combinations to implement both Maximum Power Point Tracking Methods, the results show that both Steepest Descent Method and Particle Swarm Optimization are able to track, and the results are close to stimulations, while the Steepest Descent Method has shown a better tracking efficiency.
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