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Performance improvement of dynamic PV array under partial shade conditions using M2 algorithm

Performance improvement of dynamic PV array under partial shade conditions using M2 algorithm

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Photovoltaic (PV) plants operating under the partial shade condition show an imbalance in the array irradiance and produce less output power. To counteract this problem, reconfigurable PV array or dynamic PV array (DPVA) for changing the inter-connections of PV modules to balance the irradiance distribution has been proposed previously. This study introduces a new strategy, the maximum and minimum (M2) algorithm, to identify global maximum irradiance configuration with a minimal number of interchanges among the PV modules. For the implementation of DPVA, this study introduces a double pole double throw (DPDT) switch network (SN) with less switch-count compared to a conventional SN. Simulations of PV array have been carried out on a 9 × 9 size PV array. Results are compared with the previously reported algorithms. Further, cost–benefit analysis of a 10 kWP grid-tied DPVA plant has been presented. Experimental tests on 4 × 2 size DPVA under different shade conditions are conducted to validate the proposed algorithm and DPDT SN.

References

    1. 1)
      • 1. Goud, J.S., Kalpana, R., Singh, B., et al: ‘Maximum power point tracking technique using artificial bee colony and hill climbing algorithms during mismatch insolation conditions on PV array’, IET Renew. Power Gener., 2018, 12, (16), pp. 19151922.
    2. 2)
      • 2. Basoglu, M.E., Cakir, B.: ‘Hybrid global maximum power point tracking approach for photovoltaic power optimisers’, IET Renew. Power Gener., 2018, 12, (8), pp. 875882.
    3. 3)
      • 3. Sen, T., Pragallapati, N., Agarwal, V., et al: ‘Global maximum power point tracking of PV arrays under partial shading conditions using a modified particle velocity-based PSO technique’, IET Renew. Power Gener., 2018, 12, (5), pp. 555564.
    4. 4)
      • 4. Mosa, M., Shadmand, M.B., Balog, R.S., et al: ‘Efficient maximum power point tracking using model predictive control for photovoltaic systems under dynamic weather condition’, IET Renew. Power Gener., 2017, 11, (11), pp. 14011409.
    5. 5)
      • 5. Kumar, N., Hussain, I., Singh, B., et al: ‘Peak power detection of PS solar PV panel by using WPSCO’, IET Renew. Power Gener., 2017, 11, (4), pp. 480489.
    6. 6)
      • 6. Lasheen, M., Rahman, A.K.A., Abdel-Salam, M., et al: ‘Adaptive reference voltage-based MPPT technique for PV applications’, IET Renew. Power Gener., 2017, 11, (5), pp. 715722.
    7. 7)
      • 7. da Silva, S.A.O., Sampaio, L.P., de Oliveira, F.M., et al: ‘Feed-forward DC-bus control loop applied to a single-phase grid-connected PV system operating with PSO-based MPPT technique and active power-line conditioning’, IET Renew. Power Gener., 2017, 11, (1), pp. 183193.
    8. 8)
      • 8. Belkaid, A., Gaubert, J., Gherbi, A.: ‘Design and implementation of a high-performance technique for tracking PV peak power’, IET Renew. Power Gener., 2017, 11, (1), pp. 9299.
    9. 9)
      • 9. Rajendran, S., Srinivasan, H.: ‘Simplified accelerated particle swarm optimisation algorithm for efficient maximum power point tracking in partially shaded photovoltaic systems’, IET Renew. Power Gener., 2016, 10, (9), pp. 13401347.
    10. 10)
      • 10. Horoufiany, M., Ghandehari, R.: ‘Optimal fixed reconfiguration scheme for PV arrays power enhancement under mutual shading conditions’, IET Renew. Power Gener., 2017, 11, (11), pp. 14561463.
    11. 11)
      • 11. Matam, M., Barry, V.R.: ‘Variable size dynamic PV array for small and various DC loads’, Sol. Energy, 2018, 163, pp. 581590.
    12. 12)
      • 12. Horoufiany, M., Ghandehari, R.: ‘Optimization of the Sudoku based reconfiguration technique for PV arrays power enhancement under mutual shading conditions’, Sol. Energy, 2017, 159, pp. 10371046.
    13. 13)
      • 13. Manjunath, M., Reddy, B.V., Zhao, Y., et al: ‘On-line health monitoring of PV plants’. Proc. of Energy Conversion Congress and Exposition (ECCE), October 2017, pp. 40614068.
    14. 14)
      • 14. Babu, T.S., Ram, J.P., Dragicevic, T., et al: ‘Particle swarm optimization based solar PV array reconfiguration of the maximum power extraction under partial shading conditions’, IEEE Trans. Sustain. Energy, 2017, PP, (99), pp. 11.
    15. 15)
      • 15. Deshkar, S.N., Dhale, S.B., Mukherjee, J.S., et al: ‘Solar PV array reconfiguration under partial shading conditions for maximum power extraction using genetic algorithm’, Renew. Sustain. Energy Rev., 2015, 43, pp. 102110.
    16. 16)
      • 16. Nguyen, D., Lehman, B.: ‘An adaptive solar photovoltaic array using model-based reconfiguration algorithm’, IEEE Trans. Ind. Electron., 2008, 55, (7), pp. 26442654.
    17. 17)
      • 17. Rani, B., Ilango, G., Nagamani, C.: ‘Enhanced power generation from PV array under partial shading conditions by shade dispersion using SU do KU configuration’, IEEE Trans. Sustain. Energy, 2013, 4, (3), pp. 594601.
    18. 18)
      • 18. El-Dein, M.Z.S., Kazerani, M., Salama, M.M.A.: ‘Optimal photovoltaic array reconfiguration to reduce partial shading losses’, IEEE Trans. Sustain. Energy, 2013, 4, (1), pp. 145153.
    19. 19)
      • 19. Sahu, H.S., Nayak, S.K., Mishra, S.: ‘Maximizing the power generation of a partially shaded PV array’, IEEE J. Emerg. Sel. Top. Power Electron., 2016, 4, (2), pp. 626637.
    20. 20)
      • 20. Manna, D.L., Vigni, V.L., Sanseverino, E.R., et al: ‘Reconfigurable electrical interconnection strategies for photovoltaic arrays: a review’, Renew. Sustain. Energy Rev., 2014, 33, pp. 412426.
    21. 21)
      • 21. Patnaik, B., Sharma, P., Trimurthulu, E., et al: ‘Reconfiguration strategy for optimization of solar photovoltaic array under non-uniform illumination conditions’. 37th IEEE PVSC, June 2011, pp. 18591864.
    22. 22)
      • 22. Storey, J., Wilson, P., Bagnall, D.: ‘Improved optimization strategy for irradiance equalization in dynamic photovoltaic arrays’, IEEE Trans. Power Electron., 2013, 28, (6), pp. 29462956.
    23. 23)
      • 23. Manjunath, M., Reddy, B.V., Reddy, G.A.: ‘Optimized reconfigurable solar PV battery charger using relay switch matrix’. Proc. of 7th National Power Electronics Conf., 2015, pp. 16.
    24. 24)
      • 24. Silvestre, S., da Silva, M.A., Chouder, A., et al: ‘New procedure for fault detection in grid connected PV systems based on the evaluation of current and voltage indicators’, Energy Convers. Manage., 2014, 86, pp. 241249.
    25. 25)
      • 25. Mahmoud, Y., El-Saadany, E.F.: ‘A novel mppt technique based on an image of PV modules’, IEEE Trans. Energy Convers., 2017, 32, (1), pp. 213221.
    26. 26)
      • 26. Ando, B., Baglio, S., Pistorio, A., et al: ‘Sentinella smart monitoring of photovoltaic systems at panel level’, IEEE Trans. Instrum. Meas., 2015, 64, (8), pp. 21882199.
    27. 27)
      • 27. Hu, Y., Cao, W., Wu, J., et al: ‘Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions’, IEEE Trans. Power Electron., 2014, 29, (11), pp. 56675672.
    28. 28)
      • 28. Hidalgo, F.G., Martinez, R.F., Vidal, E.F.: ‘Design of a low-cost sensor for solar irradiance’, December 2013. Available at http://oceanoptics.com/wpcontent/uploads/Fernando-Guerra-Hidalgo-Sensors-Design.pdf.
    29. 29)
      • 29. Velasco Quesada, G., Guinjoan Gispert, F., Pique Lopez, R., et al: ‘Electrical PV array reconfiguration strategy for energy extraction improvement in grid-connected PV systems’, IEEE Trans. Ind. Electron., 2009, 56, (11), pp. 43194331.
    30. 30)
      • 30. Balato, M., Costanzo, L., Vitelli, M.: ‘Series parallel PV array re configuration: maximization of the extraction of energy and much more’, Appl. Energy, 2015, 159, pp. 145160.
    31. 31)
      • 31. Orozco-Gutierrez, M.L., Spagnuolo, G., Ramirez-Scarpetta, J.M., et al: ‘Optimized configuration of mismatched photovoltaic arrays’, IEEE J. Photovoltaics, 2016, 6, (5), pp. 12101220.
    32. 32)
      • 32. Srinivasa Rao, P., Saravana Ilango, G., Nagamani, C.: ‘Maximum power from PV arrays using a fixed configuration under different shading conditions’, IEEE J. Photovoltaics, 2014, 4, (2), pp. 679686.
    33. 33)
      • 33. IEEE application guide for IEEE std 1547(tm)’, IEEE Std 1547.2-2008, April 2009, pp. 1217.
    34. 34)
      • 34. Braun, H., Buddha, S., Krishnan, V., et al: ‘Topology reconfiguration for optimization of photovoltaic array output’, Sustain. Energy Grids Netw., 2016, 6, pp. 5869.
    35. 35)
      • 35. Digikey: ‘Electronic components’, December 2017. Available at http:\\www.digikey.com.
    36. 36)
      • 36. Matam, M., Barry, V.R., Govind, A.R.: ‘Optimized reconfigurable PV array based photovoltaic water-pumping system’, Sol. Energy, 2018, 170, pp. 10631073.
    37. 37)
      • 37. E. sage: ‘10 kW solar systems prices comparison’, December 2017. Available at http:\\www.energysage.com.
    38. 38)
      • 38. Balato, M., Costanzo, L., Vitelli, M.: ‘Reconfiguration of PV modules: a tool to get the best compromise between maximization of the extracted power and minimization of localized heating phenomena’, Sol. Energy, 2016, 138, pp. 105118.
    39. 39)
      • 39. Manjunath, M., Reddy, B.V., Zhao, Y., et al: ‘On-line global maximum power point (GMPP) identification of solar PV plants’. Proc. of Applied Power Electronics Conf. and Exposition (APEC), March 2018, pp. 11091114.
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