Controlling of artificial neural network for fault diagnosis of photovoltaic array

@article{Syafaruddin2011ControllingOA,
  title={Controlling of artificial neural network for fault diagnosis of photovoltaic array},
  author={S. Syafaruddin and Engin Karatepe and Takashi Hiyama},
  journal={2011 16th International Conference on Intelligent System Applications to Power Systems},
  year={2011},
  pages={1-6}
}
High penetration of photovoltaic (PV) systems is expected to play important roles as power generation source in the near future. One of the typical deployments of PV systems is without supervisory mechanisms to monitor the physical conditions of cells or modules. In the longer term operation, the cells or modules may undergo fault conditions since they are exposure to the environment. Manually module checking is not recommended in this case because of time-consuming, less accuracy and… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-5 of 5 references

Comparison of ANN models for estimating optimal points of crystalline Silicon photovoltaic modules

E. Karatepe Syafaruddin, T. Hiyama
IEEJ Transaction on Power and Energy • 2010

Development of a suitable model for characterizing photovoltaic arrays with shaded solar cells

E. Karatepe Syafaruddin, T. Hiyama
Solar Energy • 2007

Automatic supervision and fault detection of PV systems based on power losses analysis

M. Boztepe E. Karatepe, M. Colak
Energy conversion and Management

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