Reconfiguration and Analysis of PV Array based on Particle Swarm Optimization of Solar Plant
DOI:
https://doi.org/10.2478/ecce-2022-0003Keywords:
Computational efficiency, maximum power point trackers, particle swarm optimization, photoelectricity, photovoltaic systems, power system transientsAbstract
The major shortcoming in the extraction of electrical energy occurs due to partial shading over a limited area of vast spread solar panels underpinning reduction of efficiency. A number of panels are interconnected in series and parallel to form a photovoltaic (PV) array for large power plants and a shadow over a single cell deteriorates overall performance. As a consequence, several peaks are added to the P-V curve causing hotspots in PV panels, degradation of the PV system, and collapse of tracking algorithms. In order to minimize such issues in PV panels, an effective optimization technique is developed by reconfiguring the panels which are capable of reaching the full global power point in a PV system under partial shading conditions. The study proposes particle swarm optimization (PSO) using PV characteristics of Quaid-e-Azam Solar Plant (QASP) in Punjab, Pakistan1. In PSO, electrical connections of PV modules are changed keeping their physical locations unaltered aiming to improve the performance of the PV system. After reconfiguration, the algorithm finds the best combination of PV modules by equalizing the row currents followed by the comparison of row current, voltages, and power of panels. The proposed PSO is proved to be an efficient method for reconfiguring PV modules in very less computational time by increasing the output power of shaded modules.References
F. Viola, P. Romano, E. R. Sanseverino, R. Miceli, M. Cardinale, and G. Schettino, “An economic study about the installation of PV plants reconfiguration systems in Italy,” in 3rd The International Conference on Renewable Energy Research and Applications (ICRERA), Milwaukee, WI, USA, Oct. 2014, pp. 989–994. https://doi.org/10.1109/ICRERA.2014.7016534
H. Ramyar, “Economic scheduling of microgrid based on energy management and demand response,”Electrical, Control and Communication Engineering, vol. 14, no. 2, pp. 100–107, Mar. 2018. https://doi.org/10.2478/ecce-2018-0012
P. Mohanty, G. Bhuvaneswari, R. Balasubramanian, and N. K. Dhaliwal, “MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions,” Renewable and Sustainable Energy Reviews, vol. 38(C), pp. 581–593, Oct. 2014. https://doi.org/10.1016/j.rser.2014.06.001
S. Amir and A. Morteza, “Potential of solar energy in developing countries for reducing energy-related emissions,”Renewable and Sustainable Energy Reviews, vol. 90(C), pp. 275–291, Jul. 2018. https://doi.org/10.1016/j.rser.2018.03.065
A. Patlins, A. Hnatov, S. Arhun, H. Hnatova, and V. Migal, “Study of load characteristics of various types of silicon PV panels for sustainable energy efficient road pavement,” Electrical, Control and Communication Engineering, vol. 15, no. 1, pp. 30–38, Sep. 2019. https://doi.org/10.2478/ecce-2019-0005
T. S. Babu, J. P. Ram, T. Dragicevic, M. Miyatake, F. Blaabjerg, and N. Rajasekar, “Particle swarm optimization based solar PV array reconfiguration of the maximum power extraction under partial shading conditions,”IEEE Transactions on Sustainable Energy, vol. 9, no. 1, pp. 74–85, Jan. 2018. https://doi.org/10.1109/TSTE.2017.2714905
W. Ali, H. Farooq, A. U. Rehman, Q. Awais, M. Jamil, and A. Noman, “Design considerations of stand-alone solar photovoltaic systems,” in International conference on computing, electronic and electrical engineering (ICE Cube), Quetta, Pakistan, Nov. 2018, pp. 1–6. https://doi.org/10.1109/ICECUBE.2018.8610970
S. R. Pendem and S. Mikkili, “Modeling, simulation, and performance analysis of PV array configurations (series, series-parallel, bridge-linked, and honey-comb) to harvest maximum power under various partial shading conditions,” International Journal of Green Energy, vol. 15, no. 13, pp. 795–812, Oct. 2018. https://doi.org/10.1080/15435075.2018.1529577
D. Sun, A. Athienitis, and K. D’ Avignon, “Application of semitransparent photovoltaics in transportation infrastructure for energy savings and solar electricity production: Toward novel net-zero energy tunnel design,”Progress in Photovoltaics: Research and Applications, vol. 27, pp. 1034–1044, 2019. https://doi.org/10.1002/pip.3182
A. M. Humadal, M. H. B. Sulaiman, M. Hojabri, H. M. Hamada, and M. N. Ahmed, “A review on photovoltaic array behavior, configuration strategies and models under mismatch conditions,” ARPN Journal of Engineering and Applied Sciences, vol. 11, pp. 4896–4903, 2016.
L. F. L. Villa, D. Picault, B. Raison, S. Bacha, and A. Labonne, “Maximizing the power output of partially shaded photovoltaic plants through optimization of the interconnections among its modules,”IEEE Journal of Photovoltaics, vol. 2, no. 2, pp. 154–163, Apr. 2012. https://doi.org/10.1109/JPHOTOV.2012.2185040
B. Dhanalakshmi and N. Rajasekar, “Dominance square based array reconfiguration scheme for power loss reduction in solar photovoltaic (PV) systems,” Energy Conversion and Management, vol. 156, pp. 84–102, Jan. 2018. https://doi.org/10.1016/j.enconman.2017.10.080
M. Sharma, S. Pareek, and K. Singh, “Comparative study of different configuration techniques to address the outcome of partial shading conditions on solar photovoltaic system,” IOP Conference Series: Materials Science and Engineering, vol. 594, 2019, Art no. 012031. https://doi.org/10.1088/1757-899X/594/1/012031
P. S. Rao, G. SaravanaIlango, and C. Nagamani, “Maximum power from PV arrays using a fixed configuration under different shading conditions,” IEEE Journal of Photovoltaics, vol. 4, no. 2, pp. 679–686, Mar. 2014. https://doi.org/10.1109/JPHOTOV.2014.2300239
M. Amin, J. Bailey, C. Tapia, and V. Thodimeladine, “Comparison of PV array configuration efficiency under partial shading condition,” in IEEE 43rd Photovoltaic Specialists Conference (PVSC), Portland, 2016, pp. 3704–3707. https://doi.org/10.1109/PVSC.2016.7750368
S. Liu, P. X. Liu, and X. Wang, “Stochastic small-signal stability analysis of grid-connected Photovoltaic systems,”IEEE Transactions on Industrial Electronics, vol. 63, no. 2, pp. 1027–1038, Feb. 2016. https://doi.org/10.1109/TIE.2015.2481359
E. Mele, C. Elias, and A. Ktena, “Machine learning platform for profiling and forecasting at microgrid level,” Electrical, Control and Communication Engineering, vol. 15, no. 1, pp. 21–29, Sep. 2019. https://doi.org/10.2478/ecce-2019-0004
K. Ishaque, Z. Salam, M. Amjad, and S. Mekhilef, “An improved particle swarm optimization (PSO)–based MPPT for PV with reduced steady-state oscillation,” IEEE Transactions on Power Electronics, vol. 27, no. 8, pp. 3627–3638, Aug. 2012. https://doi.org/10.1109/TPEL.2012.2185713
M. Dwivedi, G. Mehta, A. Iqbal, and H. Shekhar, “Performance enhancement of solar PV system under partial shaded condition using PSO,” in 8th Int. Conf. Comput. Commun. Netw. Technol. ICCCNT, IIT, Delhi, India, Jul. 2017, pp. 1–7. https://doi.org/10.1109/ICCCNT.2017.8204082
M. Huang, Q. Liu, and X. Liang, “The application of improved hybrid particle swarm optimization algorithm in job shop scheduling problem,” in IEEE 7th International Conference on Computer Science and Network Technology (ICCSNT), Dalian, China, Oct. 2019, pp. 49–52. https://doi.org/10.1109/ICCSNT47585.2019.8962466
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Muhammad Sheryar et al., published by Sciendo
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
