L. Sandrolini, U. Reggiani, and M. Artioli (Italy)
Renewable energy sources, photovoltaic module, equiv alent circuit, distributed computing, particle swarm opti mization.
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 com puting 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 algo rithms can thus be efficiently controlled.
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