A radial basis function neural network based approach for the electrical characteristics estimation of a photovoltaic module
- 30 September 2012
- journal article
- Published by Elsevier BV in Applied Energy
- Vol. 97, 956-961
- https://doi.org/10.1016/j.apenergy.2011.12.085
Abstract
No abstract availableThis publication has 19 references indexed in Scilit:
- An improved five-parameter model for photovoltaic modulesSolar Energy Materials and Solar Cells, 2010
- An improved thermal and electrical model for a solar photovoltaic thermal (PV/T) air collectorApplied Energy, 2010
- Photovoltaic field emulation including dynamic and partial shadow conditionsApplied Energy, 2010
- Numerical method for the extraction of photovoltaic module double-diode model parameters through cluster analysisApplied Energy, 2010
- A novel model for photovoltaic array performance predictionApplied Energy, 2007
- Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four- and five-parameter modelsApplied Energy, 2007
- Genetic algorithm-trained radial basis function neural networks for modelling photovoltaic panelsEngineering Applications of Artificial Intelligence, 2005
- Neuro-Fuzzy-Based Solar Cell ModelIEEE Transactions on Energy Conversion, 2004
- Estimation of equivalent circuit parameters of PV module and its application to optimal operation of PV systemSolar Energy Materials and Solar Cells, 2001
- Application of radial basis function networks for solar-array modelling and maximum power-point predictionIEE Proceedings - Generation, Transmission and Distribution, 2000