Butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition
2019
0 views
0 downloads
Advisor: Prof. Dr. Mehmet Tümay ; Dr. Öğr. Üyesi Tuğçe Demirdelen
Abstract (EN)
In the recent literature many soft computing techniques implemented for the MPPT of PV systems under PSC such as gray wolf optimization (GWO), particle swarm optimization (PSO) and Gravitational Search Algorithm (GSA). However, the performance of the MPP trackers still needs to be improved. The aim of this thesis is to implement a new global optimization algorithm for the MPPT of PV systems under PSC to improve the performance. For this purpose, a PV system is modelled in MATLAB/Simulink. Butterfly optimization algorithm (BOA) is implemented for three insolation scenarios on the modelled system. The results of the BOA is compared with the results of the PSO-GSA and GWO algorithm. The results showed that the BOA method is able to give high accuracy of tracking the GMPP and better speed than PSO-GSA and GWO methods.
Author
Dr. Kemal Aygül
Institution
How to Cite
Kemal Aygül (Master Thesis). Butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition, 2019, Çukurova University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Çukurova University
- Subalgebras of free associative algebras(2018)
- Production and characterization of ZnO/Cu2O based devices growing with spin coating method(2019)
- The rise of populism in liberal world order(2019)
- An evaluation of the performance of the management and development applications employed in wildlife development areas improvement area(2020)
- Investigation of the relationship between the burnout levels and perceptions of organizational climate of preschool teachers(2021)
- Temel Weitzenböck türevleri(2022)