This paper presents a distributed-computing technique based on a particle swarm optimization (PSO) algorithm for the parameter extraction of photovoltaic modules. The procedure exploits interlacing of the experimental data in order to decrease the computational load, and parallel computing of different and independent runs to collect a large amount of data in order to save computational time. The statistical instability typical of numerical data fitting algorithms can thus be efficiently controlled.
Distributed-computing approach technique for modelling the equivalent circuit of photovoltaic modules
SANDROLINI, LEONARDO;REGGIANI, UGO;
2005
Abstract
This paper presents a distributed-computing technique based on a particle swarm optimization (PSO) algorithm for the parameter extraction of photovoltaic modules. The procedure exploits interlacing of the experimental data in order to decrease the computational load, and parallel computing of different and independent runs to collect a large amount of data in order to save computational time. The statistical instability typical of numerical data fitting algorithms can thus be efficiently controlled.File in questo prodotto:
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