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Saturday, 10 July 2021

Detection of the faults in the photovoltaic array under normal and partial shading conditions

ABSTRACT:

This paper propounds a novel technique for detection of the faults in photovoltaic array by using Artificial Neural Network. By using a simulation model, the power variation under different faulty conditions such as open circuit fault, short circuit fault, and bridging fault are measured under normal and partial shading conditions. The simulated attributes are given to the Artificial Neural Network to predict the type of fault occurred in or between photovoltaic modules. Finally, three different training algorithms of Artificial Neural Network are compared for fault detection with help of mean square error as the performance parameter.

KEYWORDS:

1.      Fault detection

2.      Photovoltaic array

3.      Artificial neural network

4.      Open circuit fault

5.      Short circuit fault

6.      Bridging fault

SOFTWARE: MATLAB/SIMULINK

CONCLUSION:

In this paper, the fault detection method is proposed to detect the fault occurred in or between the PV modules. The performance of PV module has been investigated in this paper for different faults such as open circuit fault, short circuit fault and bridging fault under normal and partial shaded conditions. ANN is used to detect the faults occurred in or between PV modules under normal and partial shading conditions and it is tested with random inputs. Future work is to locating the fault in the large scale PV system.

REFERENCES:

[1] Liqun Liu, Xiaoli Meng and Chunxia Liu, “ A review of maximum power point tracking methods of PV power system at a uniform and partial shading”, International Journal on Renewable and Sustainable Energy Reviews, Vol.53, pp.1500-1507,2016.

[2] Kashif Ishaque and Zainal Salam, “ A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition”, International Journal on Renewable and Sustainable Energy Reviews, Vol.19, pp.475-488,2013.

[3] M. Sabbaghpur Arani and M.A Hejazi, “ The comprehensive study of electrical faults in PV array”, Journal of Electrical and Computer Engineering, Volume 2016.

[4] S.Saravan and N.Ramesh Babu, “Maximum power point tracking algorithms for the photovoltaic system- A review”, International Journal on Renewable and Sustainable Energy Reviews, Vol.57, pp.192-204, 2016.

[5] K.L.Lian, J.H.Jhang, and I.S.Tian, “ A maximum power point tracking method based on perturb-and-observe combined with particle swarm optimization”, IEEE Journal of Photovoltaic, Vol.4, No.2,pp.626-633,2014.