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.
2005
Proceedings of the Fifth IASTED International Conference on Power and Energy Systems
239
244
L. Sandrolini; U. Reggiani; M. Artioli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/3645
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