Characterization of Concentrating Photovoltaic modules by cooperative competitive Radial Basis Function Networks

Rivera, Antonio J.; García-Domingo, B.; Jesus, María José del; Aguilera, J.

doi:10.1016/j.eswa.2012.09.016

Cited by 27 publications

(11 citation statements)

References 44 publications

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“…Work in this area includes Rivera et al [17], Almonacid et al [18] and Fern andez et al [19]. These are applications of neural networks in order to predict the maximum power of a CPV module using several atmospheric conditions available from every meteorological station.…”

Section: Discussionmentioning

confidence: 98%

CPV module electric characterisation by artificial neural networks

et al. 2015

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a b s t r a c tConcentrating photovoltaic (CPV) is a relatively new technology with promising future expectations. However, it is at an early stage of development and it has much room for improvement. In order to gain knowledge about CPV technology, outdoor measurements are necessary to adjust models and to study the influence of the atmospheric conditions on the modules performance. In this work, multilayer perceptron models are applied to generate IeV characteristic curves of one of the most extended commercial module of concentrating photovoltaic technology, using the influential atmospheric variables as inputs to the networks. To train these networks an experiment with real measurements was carried out in Ja en, Spain, from July 2011 to June 2012. In addition to a model based on IeV curves expressed as a list of points in Cartesian coordinates, we present an alternative model trained with curves represented in polar coordinates. A previous selection of the most representative samples from the initial dataset was performed using a Kohonen self-organising map. This procedure allows the simulation of the curves even under non-frequent atmospheric conditions. Using the proposed models, it is possible to obtain the characteristic curve of other CPV modules under different meteorological conditions, with high accuracy and fidelity.

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Section: Discussionmentioning

confidence: 98%

CPV module electric characterisation by artificial neural networks

et al. 2015

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“…The results show that the ANN based-model could be used to estimate successfully the output of an HCPV module with a MBE of 0.07 %, an RMSE of 2.91 %, and an R 2 of 0.99. This approach has also been followed by Rivera et al [55]. In this case, a cooperative competitive hybrid algorithm for RBF networks was implemented.…”

Section: Application Of Anns To Estimate the Maximum Power Of A Hcpv mentioning

confidence: 95%

Applications of ANNs in the Field of the HCPV Technology

Almonacid

Mellit

Kalogirou

2015

High Concentrator Photovoltaics

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High-concentrator photovoltaic (HCPV) devices are based on the use of multijunctions solar cells and optical devices. Therefore, the electrical modelling of an HCPV device presents a great level of complexity. Several artificial neural network (ANN)-based models have been developed to try to address this issue. In this chapter, a review of the developed ANN-based models developed to try to address some issues related with the field of high concentrator PV technology is reported. In addition, the results obtained from the application of some of these models to estimate the electrical parameters of an HCPV module-such as maximum power, short-circuit current, and open-circuit voltage-are presented. The results show that the ANNs are a useful tool for modelling HCPV applications.

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“…To date, numerous companies have started a CPV business, facing one of the biggest problem of this technology: the lack of agreed international standards in the CPV power rating and characterization [2]- [4]. In fact, the absence of CPV standardization let manufacturers free to use the test conditions they prefer for rating the nominal power of their CPV modules, making difficult the performance comparison [3]. Presently, only few nationwide standards define Concentrating Standard Test Conditions (CSTC).…”

Section: Introductionmentioning

confidence: 99%

“…In the technical literature, many studies [3], [7]- [9] consider this standard as the reference one for reporting the performance of a CPV module at standard conditions, lacking internationally approved CSTC which refer to. In order to overcome this problem, the IEC TC 82 is developing new CPV standards (IEC 62670 series) which aim to define the testing and rating procedures for CPV modules and to provide wellestablished CSTC.…”

Section: Introductionmentioning

confidence: 99%

Concentrator photovoltaic standards: Experimental analyses of technical requirements

Damiano

Marongiu

Musio

et al. 2013

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

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The continuing development and the increasing diffusion of concentrator photovoltaic (CPV) systems highlight the lack of specific international standards in the CPV power rating and characterization field. Presently, the only reference standard for CPV cells and modules is the IEC 62108, which does not impose minimum requirements for solar trackers and simulators used in the qualification process of CPV modules. Nevertheless, the overall quality of CPV tests is strictly associated to the technical specifications of these devices. The aim of this paper is to define optical and radiometric properties of solar simulators and the pointing accuracy of solar trackers, required for testing CPV devices and rating their performance. The results of experimental analyses on real CPV systems have been reported, highlighting the criticalities of indoor and outdoor CPV characterization. Finally an outdoor light soaking test, executed under MPPT conditions, has been proposed for the qualification process of high concentrating photovoltaic devices

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Characterization of Concentrating Photovoltaic modules by cooperative competitive Radial Basis Function Networks

Cited by 27 publications

References 44 publications

CPV module electric characterisation by artificial neural networks

CPV module electric characterisation by artificial neural networks

Applications of ANNs in the Field of the HCPV Technology

Concentrator photovoltaic standards: Experimental analyses of technical requirements

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