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Parameter extraction for dynamic PV thermal model using particle swarm optimisation
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AI
DOI：10.1016/j.applthermaleng.2016.01.164.png)
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Abstract
En 中文
A dynamic thermal model for a photovoltaic (PV) module has been developed, considering all possible mechanisms of heat transfer between the module and its environment. The particle swarm optimisation (PSO) technique is applied for extraction of model parameters from experimental data. The model is then used to predict the PV module temperature variation with time on different days of the year. It is shown that the predicted temperature tracks the experimentally measured temperature very closely for a variety of atmospheric conditions at the location of installation. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords:
PV module dynamic thermal model
Particle swarm optimisation (PSO)
Parameter extraction
Journal
IF:
6.9
Papers:
2.7W
Citations:
10.6W