Araştırma Makalesi
Yıl 2021,
Cilt: 25 Sayı: 4, 1075 - 1085, 30.08.2021
Öz
Kaynakça
- K. K. Tse, M. T. Ho, H. S. -H. Chung, and S. Y. Hui, “A novel maximum power point tracker for PV panels using switching frequency modulation,” IEEE Transactions on Power Electronics, vol. 17, no. 6, pp. 980-989, 2002.
- O. Ezinwanne, F. Zhongwen, and L. Zhijun, “Energy performance and cost comparison of MPPT techniques for photovoltaics and other applications,” Energy Procedia, vol. 107, pp. 297-303, 2017.
- S. E. Babaa, M. Armstrong, V. Pickert, “Overview of maximum power point tracking control methods for PV systems,” Journal of Power and Energy Engineering, vol. 2, no. 8, pp. 59-72, 2014.
- F. D. Murdianto, M. Z. Efendi, R. E. Setiawan, and A. S. L. Hermawan, “Comparison method of MPSO, FPA, and GWO algorithm in MPPT SEPIC converter under dynamic partial shading condition,” 2017 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA), Surabaya, pp. 315-320, 2017.
- N. Khanam, B. H. Khan, and T. Imtiaz, “Maximum power extraction of solar PV system using meta-heuristic MPPT techniques: A comparative study,” 2019 International Conference on Electrical, Electronics and Computer Engineering (UPCON), Aligarh, pp. 1-6, 2019.
- M. A. Dirmawan, Suhariningsih, and R. Rakhmawati, “The comparison performance of MPPT perturb and observe, fuzzy logic controller, and flower pollination algorithm in normal and partial shading condition,” 2020 International Electronics Symposium (IES), Surabaya, pp. 7-13, 2020.
- A. Dolara, R. Faranda, S. Leva, “Energy comparison of seven MPPT techniques for PV systems,” Journal of Electromagnetic Analysis and Applications, vol. 1, no. 3, pp. 152-162, 2009.
- M. Miyatake, M. Veerachary, F. Toriumi, N. Fujii, and H. Ko, “Maximum power point tracking of multiple photovoltaic arrays: A PSO approach,” IEEE Transactions on Aerospace and Electronic Systems, vol. 47, no. 1, pp. 367-380, 2011.
- A. M. Eltamaly, M. S. Al-Saud, and A. G. Abokhalil, “A novel bat algorithm strategy for maximum power point tracker of photovoltaic energy systems under dynamic partial shading,” IEEE Access, vol. 8, pp. 10048-10060, 2020.
- J. Ding, Q. Wang, Q. Zhang, Q. Ye, and Y. Ma, “A hybrid particle swarm optimization-cuckoo search algorithm and its engineering applications,” Mathematical Problems in Engineering, vol. 2019, pp. 1-12, 2019.
- P. Dhivya, and K. R. Kumar, “MPPT based control of sepic converter using firefly algorithm for solar PV system under partial shaded conditions,” 2017 International Conference on Innovations in Green Energy and Healthcare Technologies (IGEHT), Coimbatore, pp. 1-8, 2017.
- W. Xiao, “Photovoltaic power system modeling, design, and control,” Chennai, Wiley, 2017.
- R. Faranda, and S. Leva, “Energy comparison of MPPT techniques for PV Systems,” WSEAS Transactions on Power Systems, vol. 3, no. 6, pp. 446-455, 2008.
- M. R. Shaikh, S. Shaikh, S. Waghmare, S. Labade, and A. Tekale, “A review paper on electricity generation from solar energy,” International Journal for Research in Applied Science and Engineering Technology, vol. 5, no. 9, pp. 1884-1889, 2017.
- R. Anand, S. D, and B. Kumar, “Global maximum power point tracking for PV array under partial shading using cuckoo search,” 2020 IEEE 9th Power India International Conference (PIICON), Sonepat, pp. 1-6, 2020.
- R.-E. Precup, T. Kamal, and S. Z. Hassan, “Solar photovoltaic power plants - Advanced control and optimization techniques,” Singapore, Springer, 2019.
- K. Aygül, “Butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition,” Adana, Cukurova University, 2019.
- M. V. Rocha, L. P. Sampaio, and S. A. Silva, “Comparative analysis of ABC, Bat, GWO and PSO algorithms for MPPT in PV systems,” 8th International Conference on Renewable Energy Research and Applications, Brasov, pp. 347-352, 2019.
- G. Dilep, and S. Singh, “An improved particle swarm optimization based maximum power point tracking algorithm for PV system operating under partial shading conditions,” Solar Energy, vol. 158, pp. 1006-1015, 2017.
- H. Chaieb, and A. Sakly, “Review and comparison of BAT and PSO MPPT’s based algorithms for photovoltaic system,” WSEAS Transactions on Power Systems, vol. 13, pp. 108-117, 2018.
- A. M. Kamoona, J. C. Patra and A. Stojcevski, “An enhanced cuckoo search algorithm for solving optimization problems,” 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, pp. 1-6, 2018.
- J. Ahmed, and Z. Salam, “A soft computing MPPT for PV system based on cuckoo search algorithm,” 4th International Conference on Power Engineering, Energy and Electrical Drives, Istanbul, pp. 558-562, 2013.
- M. I. Mosaad, M. O. el-Raouf, M. A. Al-Ahmar, and F. A. Banakher, “Maximum power point tracking of PV system based cuckoo search algorithm; review and comparison,” Energy Procedia, vol. 162, pp. 117-126, 2019.
- T. P. Dao, “Cuckoo search algorithm: Statistical-based optimization approach and engineering applications,” Singapore, Springer, 2021.
- A. Brabazon, and S. McGarraghy, “Foraging-inspired optimisation algorithms,” Dublin, Springer, 2018.
- K. Sundareswaran, S. Peddapati, and S. Palani, “MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies,” IEEE Transactions on Energy Conversion, vol. 29, no. 2, pp. 463-472, 2014.
- M. Mohanty, S. Selvakumar, C. Koodalsamy, and S. Simon, “Global maximum operating point tracking for PV system using fast convergence firefly algorithm,” Turkish Journal of Electrical Engineering & Computer Sciences, vol. 27, pp. 4640-4658, 2019.
- L. N. Palupi, T. Winarno, A. Pracoyo, and L. Ardhenta, “Adaptive voltage control for MPPT-firefly algorithm output in PV system,” IOP Conference Series: Materials Science and Engineering, East Java, vol. 732, pp. 1-9, 2020.
Comparison of Maximum Power Point Tracking Methods Using Metaheuristic Optimization Algorithms for Photovoltaic Systems
Öz
The maximum power value that can be obtained from photovoltaic systems can change continuously due to environmental conditions such as temperature, sunlight and partial shading. Direct current-direct current (DC-DC) converters and maximum power point tracking (MPPT) algorithms are required, especially in cases of partial shading, in order for the photovoltaic systems to operate at the maximum power point, that is, to draw the maximum possible power value from the system. In this study, simulation studies has been carried out for two different partially shaded scenarios using the boost-type DC-DC converter and MPPT algorithm in the PV array consisting of 3 panels connected in series. In the simulation studies, the output powers obtained by the application of particle swarm optimization, cuckoo optimization, bat optimization and firefly optimization techniques as MPPT algorithm has been compared. In the scenarios examined, the firefly optimization algorithm reached the maximum power point faster, and it has been observed that the firefly optimization method obtained the highest average power at the end of the simulation periods.
Anahtar Kelimeler
Photovoltaic system partially shaded condition MPPT optimization algorithms DC-DC converter
Kaynakça
- K. K. Tse, M. T. Ho, H. S. -H. Chung, and S. Y. Hui, “A novel maximum power point tracker for PV panels using switching frequency modulation,” IEEE Transactions on Power Electronics, vol. 17, no. 6, pp. 980-989, 2002.
- O. Ezinwanne, F. Zhongwen, and L. Zhijun, “Energy performance and cost comparison of MPPT techniques for photovoltaics and other applications,” Energy Procedia, vol. 107, pp. 297-303, 2017.
- S. E. Babaa, M. Armstrong, V. Pickert, “Overview of maximum power point tracking control methods for PV systems,” Journal of Power and Energy Engineering, vol. 2, no. 8, pp. 59-72, 2014.
- F. D. Murdianto, M. Z. Efendi, R. E. Setiawan, and A. S. L. Hermawan, “Comparison method of MPSO, FPA, and GWO algorithm in MPPT SEPIC converter under dynamic partial shading condition,” 2017 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA), Surabaya, pp. 315-320, 2017.
- N. Khanam, B. H. Khan, and T. Imtiaz, “Maximum power extraction of solar PV system using meta-heuristic MPPT techniques: A comparative study,” 2019 International Conference on Electrical, Electronics and Computer Engineering (UPCON), Aligarh, pp. 1-6, 2019.
- M. A. Dirmawan, Suhariningsih, and R. Rakhmawati, “The comparison performance of MPPT perturb and observe, fuzzy logic controller, and flower pollination algorithm in normal and partial shading condition,” 2020 International Electronics Symposium (IES), Surabaya, pp. 7-13, 2020.
- A. Dolara, R. Faranda, S. Leva, “Energy comparison of seven MPPT techniques for PV systems,” Journal of Electromagnetic Analysis and Applications, vol. 1, no. 3, pp. 152-162, 2009.
- M. Miyatake, M. Veerachary, F. Toriumi, N. Fujii, and H. Ko, “Maximum power point tracking of multiple photovoltaic arrays: A PSO approach,” IEEE Transactions on Aerospace and Electronic Systems, vol. 47, no. 1, pp. 367-380, 2011.
- A. M. Eltamaly, M. S. Al-Saud, and A. G. Abokhalil, “A novel bat algorithm strategy for maximum power point tracker of photovoltaic energy systems under dynamic partial shading,” IEEE Access, vol. 8, pp. 10048-10060, 2020.
- J. Ding, Q. Wang, Q. Zhang, Q. Ye, and Y. Ma, “A hybrid particle swarm optimization-cuckoo search algorithm and its engineering applications,” Mathematical Problems in Engineering, vol. 2019, pp. 1-12, 2019.
- P. Dhivya, and K. R. Kumar, “MPPT based control of sepic converter using firefly algorithm for solar PV system under partial shaded conditions,” 2017 International Conference on Innovations in Green Energy and Healthcare Technologies (IGEHT), Coimbatore, pp. 1-8, 2017.
- W. Xiao, “Photovoltaic power system modeling, design, and control,” Chennai, Wiley, 2017.
- R. Faranda, and S. Leva, “Energy comparison of MPPT techniques for PV Systems,” WSEAS Transactions on Power Systems, vol. 3, no. 6, pp. 446-455, 2008.
- M. R. Shaikh, S. Shaikh, S. Waghmare, S. Labade, and A. Tekale, “A review paper on electricity generation from solar energy,” International Journal for Research in Applied Science and Engineering Technology, vol. 5, no. 9, pp. 1884-1889, 2017.
- R. Anand, S. D, and B. Kumar, “Global maximum power point tracking for PV array under partial shading using cuckoo search,” 2020 IEEE 9th Power India International Conference (PIICON), Sonepat, pp. 1-6, 2020.
- R.-E. Precup, T. Kamal, and S. Z. Hassan, “Solar photovoltaic power plants - Advanced control and optimization techniques,” Singapore, Springer, 2019.
- K. Aygül, “Butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition,” Adana, Cukurova University, 2019.
- M. V. Rocha, L. P. Sampaio, and S. A. Silva, “Comparative analysis of ABC, Bat, GWO and PSO algorithms for MPPT in PV systems,” 8th International Conference on Renewable Energy Research and Applications, Brasov, pp. 347-352, 2019.
- G. Dilep, and S. Singh, “An improved particle swarm optimization based maximum power point tracking algorithm for PV system operating under partial shading conditions,” Solar Energy, vol. 158, pp. 1006-1015, 2017.
- H. Chaieb, and A. Sakly, “Review and comparison of BAT and PSO MPPT’s based algorithms for photovoltaic system,” WSEAS Transactions on Power Systems, vol. 13, pp. 108-117, 2018.
- A. M. Kamoona, J. C. Patra and A. Stojcevski, “An enhanced cuckoo search algorithm for solving optimization problems,” 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, pp. 1-6, 2018.
- J. Ahmed, and Z. Salam, “A soft computing MPPT for PV system based on cuckoo search algorithm,” 4th International Conference on Power Engineering, Energy and Electrical Drives, Istanbul, pp. 558-562, 2013.
- M. I. Mosaad, M. O. el-Raouf, M. A. Al-Ahmar, and F. A. Banakher, “Maximum power point tracking of PV system based cuckoo search algorithm; review and comparison,” Energy Procedia, vol. 162, pp. 117-126, 2019.
- T. P. Dao, “Cuckoo search algorithm: Statistical-based optimization approach and engineering applications,” Singapore, Springer, 2021.
- A. Brabazon, and S. McGarraghy, “Foraging-inspired optimisation algorithms,” Dublin, Springer, 2018.
- K. Sundareswaran, S. Peddapati, and S. Palani, “MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies,” IEEE Transactions on Energy Conversion, vol. 29, no. 2, pp. 463-472, 2014.
- M. Mohanty, S. Selvakumar, C. Koodalsamy, and S. Simon, “Global maximum operating point tracking for PV system using fast convergence firefly algorithm,” Turkish Journal of Electrical Engineering & Computer Sciences, vol. 27, pp. 4640-4658, 2019.
- L. N. Palupi, T. Winarno, A. Pracoyo, and L. Ardhenta, “Adaptive voltage control for MPPT-firefly algorithm output in PV system,” IOP Conference Series: Materials Science and Engineering, East Java, vol. 732, pp. 1-9, 2020.
Toplam 28 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Elektrik Mühendisliği |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 30 Ağustos 2021 |
| Gönderilme Tarihi | 11 Mayıs 2021 |
| Kabul Tarihi | 14 Temmuz 2021 |
| Yayımlandığı Sayı | Yıl 2021 Cilt: 25 Sayı: 4 |
Kaynak Göster
Cited By
Developing an optimization model for minimizing solid waste collection costs
Sakarya University Journal of Science
https://doi.org/10.16984/saufenbilder.1241012
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.