PV output power enhancement using meta-heuristic crow search algorithm under uniform and shading condition

B. Maniraj, A. Peer Fathima, Stella Morris

Abstract


In uniform condition, the power-voltage (P_V) curve has unique global peak and no local peaks. But in non-uniform or shading condition P_V curve has many local peaks with a unique global peak. Therefore, tracking the global peak is key factor to improve the photo voltaic (PV) performance under uniform and shading conditions. To track global peak, maximum power point tracking (MPPT) controller is mandatory requirement.  Numerous soft computing algorithms are developed and explained in past decades. But the ability to track global maximum peak (GMP) is not assured under shading conditions due to trapping with local peaks instead of global peaks. In this research article, a new meta–heuristic crow search algorithm (CSA) is developed and extracted GMP under uniform and shading conditions of PV module. The highlight of CSA is it works on dual mode search ability namely intensification and diversification. Because of this dual mode operation, the local peak convergence problem is solved and it tracks GMP very fast. The experimental outcomes show that the CSA technique provides higher efficiency and faster tracking time.


Keywords


Maximum Power Point Tracking (MPPT), Photovoltaic (PV), Global Maximum Power (GMP), Crow Search Algorithm (CSA)

Full Text:

PDF

References


https://powermin.gov.in/en/content/power-sector- glance-all-India

Yousri, D., Babu, T.S., Allam, D., Ramachandaramurthy, V.K., Etiba, M.B., “A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions”, IEEE Access, Vol.7. pp.121432–121445, 2019.

Abdelkader Hadj Dida, Mohamed Bourahla, Ertan H. Bulent, Mohamed Bekhti, “ Analytical Modelling, Simulation and Comparative Study of Multi-junction Solar Cells Efficiency”, International journal of renewable energy Research, Vol. 8, pp. 1824-32 , 2018.

Kumari, P.A., Geethanjali, P., “Parameter estimation for photovoltaic system under normal and partial shading conditions. A survey”, Renew. Sustain. Energy Rev. Vol. 84, pp. 1–11, 2018.

Daraban, S., Petreus, D., Morel, C., “A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading”, Energy, Vol. 74, pp. 374–388, 2014,

Lyden, S., Haque, M.E., “A Simulated Annealing Global Maximum Power Point Tracking Approach for PV Modules under Partial Shading Conditions”, IEEE Trans. Power Electron. Vol. 31, pp. 4171–4181, 2016.

Saad A. Mohamed Abdelwahab, Abdallah Mohamed Hamada , Walid S.E. Abdellatif, “Comparative analysis of the modified Perturb & Observe with different MPPT techniques for grid connected systems”, International journal of renewable energy Research, Vol. 10, pp. 155-164, 2020.

Santi Agatino Rizzo, “Enhanced Hybrid Global MPPT Algorithm for PV systems operating under Fast Changing Partial Shading Conditions”, International journal of renewable energy Research, Vol. 8, pp. 221-229, 2018

D’Ambrosio, A., Spiller, D., Curti, F., “Improved magnetic charged system search optimization algorithm with application to satellite formation flying. Eng. Appl. Artif. Intell. Vol. 89, pp. 103473, 2020

Clerc, M., “Particle Swarm Optimization. Part. Swarm Optim”, pp. 1942–1948, 2010

Nugraha, D.A., Lian, K.L., Suwarno, “A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System. 2018 IEEE Electr. Power Energy Conf. EPEC, pp. 173–182, 2018.

Prasad, R., Ali, M., Kwan, P., Khan, H., “Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation”, Appl. Energy, Vol. 236, pp. 778–792, 2019.

Duman, S., Kahraman, H.T., Sonmez, Y., Guvenc, U., Kati, M., Aras, S., “A powerful meta-heuristic search algorithm for solving global optimization and real-world solar photovoltaic parameter estimation problems”, Eng. Appl. Artif. Intell. Vol. 111, pp. 1047-63, 2020.

Kumar, N., Hussain, I., Singh, B., Panigrahi, B.K., “Peak power detection of PS solar PV panel by using WPSCO”, IET Renew. Power Gener.Vol. 11, pp. 480–489, 2017.

Mao, M., Cui, L., Zhang, Q., Guo, K., Zhou, L., Huang, H., “Classification and summarization of solar photovoltaic MPPT techniques: A review based on traditional and intelligent control strategies”, Energy Reports, Vol. 6, pp. 1312–1327, 2020.

Maniraj, B., Peer Fathima, A., “PV output power enhancement using whale optimization algorithm under normal and shading conditions” International journal of renewable energy Research, Vol. 10, pp. 1542–1543, 2020.

V. Balaji, A. Peer Fathima, “Hybrid Algorithm for Tracking Maximum Power in Solar Pv Array under Partially Shaded Condition,” International Journal of Power and Energy Systems. Vol. 39, no. 3, pp. 166-176, 2019.

Hussien, A.G., Amin, M., Wang, M., Liang, G., Alsanad, A., Gumaei, A., Chen, H., “Crow search algorithm: Theory, recent advances, and applications”, IEEE Access Vol. 8, pp. 173548–173565, 2020.




DOI (PDF): https://doi.org/10.20508/ijrer.v13i1.13512.g8666

Refbacks

  • There are currently no refbacks.


Online ISSN: 1309-0127

Publisher: Gazi University

IJRER is cited in SCOPUS, EBSCO, WEB of SCIENCE (Clarivate Analytics);

IJRER has been cited in Emerging Sources Citation Index from 2016 in web of science.

WEB of SCIENCE in 2025; 

h=35,

Average citation per item=6.59

Last three Years Impact Factor=(1947+1753+1586)/(146+201+78)=5286/425=12.43

Category Quartile:Q4