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Effective utilisation and efficient maximum power extraction in partially shaded photovoltaic systems using minimum-distance-average-based clustering algorithm

Effective utilisation and efficient maximum power extraction in partially shaded photovoltaic systems using minimum-distance-average-based clustering algorithm

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The reduction in power depends on module interconnection scheme and shading pattern. Different interconnection schemes are used to reduce the losses caused by partial shading. This study presents a minimum-distance-average-based clustering algorithm for the photovoltaic (PV) arrays that can improve the PV power under different shading conditions. The PV array is configured based on a novel clustering algorithm in wireless sensor networks based on sensor node deployment location coordinates. Various cases such as short narrow, short wide, long narrow and long wide have been analysed and their performances were discussed. The proposed method facilitates maximum power extraction by distributing the effect of shading over the entire array thereby reducing the mismatch losses caused by partial shading conditions. The performance of the system is investigated for different shading conditions. Also Monte Carlo estimator was used to improve the impact of the investigation by varying solar irradiance values and the results are presented to show the successful working of the proposed scheme.

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
      • 12. Jadidoleslamy, H.: ‘A novel clustering algorithm for homogenous and large-scale wireless sensor networks: based on sensor nodes deployment location coordinates’, Int. J. Comput. Sci. Netw. Secur., 2014, 14, (2), pp. 97109.
    13. 13)
    14. 14)
    15. 15)
      • 15. Liliana, M., Arboleda, C., Nidal, N.: ‘Comparison of clustering algorithms and protocols for wireless sensor networks’. Proc. IEEE CCECE/CCGEI 2006, May 2006, pp. 17871792.
    16. 16)
    17. 17)
      • 17. Loscri, V., Morabito, G., Marano, S.: ‘A two-level hierarchy for low-energy adaptive clustering hierarchy’. Proc. IEEE VTC, 2005, pp. 18091813.
    18. 18)
      • 18. Youssef, A., Younis, M., Agrawala, A.: ‘Distributed formation of overlapping multi-hop clusters in wireless sensor networks’. Proc. 49th Annual IEEE Global Communication Conf., November 2006, pp. 12311239.
    19. 19)
    20. 20)
      • 20. Fishman, G.S.: ‘Monte Carlo: concepts, algorithms and applications’ (Springer-Verlag, New York, 1996, 1st edn.).
    21. 21)
      • 21. Rubinstein, R.Y., Dirk, P.: ‘Simulation and the Monte Carlo method’ (John Wiley & Sons, New York, 2007, 2nd edn.).
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