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EnglishIn this paper a distributed-computing technique to extract photovoltaic module parameters is presented. The proposed procedure is based on a particle swarm optimization (PSO) strategy that 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 results show that the choice of the search range width and the rules to accept/refuse possible solutions strongly influences the parameter extraction and involves exploiting further statistical analysis to control the statistical instability typical of numerical data fitting algorithms.
| Titolo: | Parameter extraction of photovoltaic modules with a distributed computing approach | |
| Autore/i: | M. Artioli; REGGIANI, UGO; SANDROLINI, LEONARDO | |
| Autore/i Unibo: | ||
| Anno: | 2005 | |
| Titolo del libro: | Proceedings of the 20th European Photovoltaic Solar Energy Conference and Exhibition | |
| Pagina iniziale: | 274 | |
| Pagina finale: | 277 | |
| Abstract: | In this paper a distributed-computing technique to extract photovoltaic module parameters is presented. The proposed procedure is based on a particle swarm optimization (PSO) strategy that 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 results show that the choice of the search range width and the rules to accept/refuse possible solutions strongly influences the parameter extraction and involves exploiting further statistical analysis to control the statistical instability typical of numerical data fitting algorithms. | |
| Data prodotto definitivo in UGOV: | 22-feb-2006 | |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
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