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Çita optimizasyon algoritması kullanarak kısmi gölgelenme altındaki fotovoltaik sistemlerde maksimum güç noktası izleyicisinin tasarlanması

Year 2025, Volume: 40 Issue: 1, 555 - 572

Murat Çıkan

https://doi.org/10.17341/gazimmfd.1183267

Abstract

Fotovoltaik (PV) sistemler ile enerji üretimi, yenilenebilir enerji kaynakları arasında önemli bir paya sahiptir. Panellerin enerji verimliliği %11-28 arasında değişmektedir. PV sistemler kullanılarak üretilen enerjinin maksimum verimi sağlaması istenir. Işınım (radyasyon) ve sıcaklık değerleri güneş enerji sistemlerinde (GES) üretilen enerjinin miktarını belirleyen baskın iki atmosferik faktördür. Panellerdeki kirlenme, gökyüzünde oluşan bulutlanma ve çevresel faktörler gibi çeşitli etmenler panellerin maruz kaldığı ışınım değerlerinin düşmesine sebep olmaktadır. Bu durum genel olarak kısmi ya da parçalı gölgelenme (PSC) olarak adlandırılır. Farklı ışınım değerleri altında çalışan PV dizilerinde, bir tane global maksimum güç noktası (GMPP) ve birden fazla yerel maksimum güç noktası (LMPP) oluşmaktadır. PSC altında çalışan PV sistemlerde, maksimum güç çıkısının elde edilebilmesi için, PV dizilerinin GMPP’de çalıştırılması gerekmektedir. Bu amaç için, literatürde farklı maksimum güç noktası izleyici (MPPT) tasarımları ve optimizasyon algoritmaları geliştirilmiştir. Bu çalışmada maksimum güç noktasının takibi için farklı meta-sezgisel arama algoritmalarından yararlanılmıştır. Kullanılan arama algoritmaları sırasıyla parçacık sürü optimizasyon algoritması (PSO), gri kurt algoritması (GWO) ve çita optimizasyon (CO) arama algoritmasıdır. Maksimum güç noktasının izlenmesi için gerekli olan matematiksel model Matlab ortamında kod olarak yazıldı. Elde edilen sonuçlar Matlab/Simulink ve gerçek zamanlı ölçüm verileri ile karşılaştırılmıştır. Önerilen çita optimizasyon algoritmasının, test edilen diğer algoritmalara göre üstünlüğü 15`ten farklı istatiksel yöntem kullanılarak gösterilmiştir.

Keywords

Kısmi gölgelenme güneş enerji sistemleri çita arama algoritması maksimum güç noktası izleyici tasarımı.

References

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  • 2. Gosumbonggot J., Nguyen D.-D., Fujita G., Partial Shading and Global Maximum Power Point Detections Enhancing MPPT for Photovoltaic Systems Operated in Shading Condition, 53rd International Universities Power Engineering Conference (UPEC), Glasgow, UK, 1–6, 2018.
  • 3. Ishaque K., Salam Z., Amjad M., Mekhilef S., An Improved Particle Swarm Optimization (PSO)–Based MPPT for PV With Reduced Steady-State Oscillation, IEEE Transactions on Power Electronics, 27 (8), 3627–3638, 2012.
  • 4. Rezk H., A comprehensive sizing methodology for stand-alone battery-less photovoltaic water pumping system under the Egyptian climate, Cogent Engineering, 3 (1), 1-12, 2016.
  • 5. Rezk H., Dousoky G. M., Technical and economic analysis of different configurations of stand-alone hybrid renewable power systems – A case study, Renewable and Sustainable Energy Reviews, 62, 941–953, 2016.
  • 6. Aygül K., Cikan M., Demirdelen T., Tumay M., Butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 45 (3), 1–19, 2019.
  • 7. Ponkarthik N., Kalidasa Murugavel K., Performance enhancement of solar photovoltaic system using novel Maximum Power Point Tracking, International Journal of Electrical Power & Energy Systems, 60, 1–5, 2014.
  • 8. Ramli M. Z., Salam Z., Analysis and experimental validation of partial shading mitigation in photovoltaic system using integrated DC-DC converter with maximum power point tracker, IET Renewable Power Generation, 13 (13), 2356–2366, 2019.
  • 9. Liu Y.-H., Huang S.-C., Huang J.-W., Liang W.-C., A Particle Swarm Optimization-Based Maximum Power Point Tracking Algorithm for PV Systems Operating Under Partially Shaded Conditions, IEEE Transactions on Energy Conversion, 27 (4), 1027–1035, 2012.
  • 10. Xiao W., Dunford W. G., A modified adaptive hill climbing MPPT method for photovoltaic power systems, IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551), Aachen, Germany, 1957-1963, 2004.
  • 11. Üzmuş H., Genç N., Çelik M. A., DSP based hybrid control method for PV systems, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (4), 2251–2260, 2023.
  • 12. Liu F., Duan S., Liu F., Liu B., Kang Y., A Variable Step Size INC MPPT Method for PV Systems, IEEE Transactions on Industrial Electronics, 55 (7), 2622–2628, 2008.
  • 13. Safari A., Mekhilef S., Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter, IEEE Transactions on Industrial Electronics, 58 (4), 1154–1161, 2011.
  • 14. Mei Q., Shan M., Liu L., Guerrero J. M., A Novel Improved Variable Step-Size Incremental-Resistance MPPT Method for PV Systems, IEEE Transactions on Industrial Electronics, 58 (6), 2427–2434, 2011.
  • 15. Kimball J. W., Krein P. T., Discrete-Time Ripple Correlation Control for Maximum Power Point Tracking, IEEE Transactions on Power Electronics, 23 (5), 2353–2362, 2008.
  • 16. Chen K., Tian S., Cheng Y., Bai L., An Improved MPPT Controller for Photovoltaic System Under Partial Shading Condition, IEEE Transactions on Sustainable Energy, 5 (3), 978–985, 2014.
  • 17. Thakkar N., Cormode D., A. Lonij V. P., Pulver S., Cronin A. D., A simple non-linear model for the effect of partial shade on PV systems, 35th IEEE Photovoltaic Specialists Conference, Honolulu, HI, USA, 2321–2326, 2010.
  • 18. Refaat A., Khalifa A. E., Elsakka M. M., Elhenawy Y., Kalas A., Elfar M. H., A novel metaheuristic MPPT technique based on enhanced autonomous group Particle Swarm Optimization Algorithm to track the GMPP under partial shading conditions - Experimental validation, Energy Conversion and Management, 287, 117124, 2023.
  • 19. Hamza Zafar M., Noman M.K., Mirza A.F., Mansoor M., Akhtar N., Qadir M.U., Khan N.A., Moosavi S.K.R., A novel meta-heuristic optimization algorithm based MPPT control technique for PV systems under complex partial shading condition, Sustainable Energy Technologies and Assessments, 47, 101367, 2021.
  • 20. Guo K., Cui L., Mao M., Zhou L., Zhang Q., An Improved Gray Wolf Optimizer MPPT Algorithm for PV System with BFBIC Converter Under Partial Shading, IEEE Access, 8, 103476–103490, 2020.
  • 21. Cikan M., Dogansahin K., A Comprehensive Evaluation of Up-to-Date Optimization Algorithms on MPPT Application for Photovoltaic Systems, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 45 (4), 10381–10407, October 2023.
  • 22. Dagal I., Akın B., Akboy E., MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink, Scintific Reports, 12 (1), 2664, 2022.
  • 23. Manna S., Singh D.K., Akella A.K., Kotb H., AboRas K.M., Zawbaa H.M., Kamel S., Design and implementation of a new adaptive MPPT controller for solar PV systems, Energy Reports, 9, 1818–1829, 2023.
  • 24. Karafil A., Comparison of the various irregular pulse density modulation (PDM) control pattern lengths for resonant converter with photovoltaic (PV) integration, Journal of the Faculty of Engineering and Architecture of Gazi University, 36 (3), 1595–1611, 2021.
  • 25. Akbari M. A., Zare M., Azizipanah-abarghooee R., Mirjalili S., Deriche M., The cheetah optimizer: a nature-inspired metaheuristic algorithm for large-scale optimization problems, Scientific Report, 12 (1), 10953, 2022.
  • 26. Mirjalili S., Mirjalili S. M., Lewis A., Grey Wolf Optimizer, Advances in Engineering Software, 69, 46–61, 2014.
  • 27. Mirjalili S., Hashim S. Z. M., A new hybrid PSOGSA algorithm for function optimization, International Conference on Computer and Information Application, Tianjin, China, 374–377, 2010.
  • 28. De Soto W., Klein S. A., Beckman W. A., Improvement and validation of a model for photovoltaic array performance, Solar Energy, 80(1), 78–88, 2006.
  • 29. Tian H., Mancilla-david F., Ellis K., Jenkins P., Muljadi E., A Detailed Performance Model for Photovoltaic Systems Preprint, Solar Energy Journal, 2012.
  • 30. Hejri M., Mokhtari H., Azizian M. R., Söder L., An analytical-numerical approach for parameter determination of a five-parameter single-diode model of photovoltaic cells and modules, International Journal of Sustainable Energy, 35 (4), 396–410, 2016.
  • 31. Ioinovici A., Modeling DC-DC Converters, Power Electronics and Energy Conversion Systems, 161–368, 2013.
  • 32. Ayop R., Tan C. W., Design of boost converter based on maximum power point resistance for photovoltaic applications, Solar Energy, 160, 322–335, 2017.
  • 33. Kyocera, High-efficiency multi-crystal photovoltaic module KC200GT, PV datasheet, 2, 2009.
  • 34. Seyedmahmoudian M., Mekhilef S., Rahmani R., Yusof R., Renani E. T., Analytical Modeling of Partially Shaded Photovoltaic Systems, Energies, 6 (1), 128–144, 2013.
  • 35. Shaffer R. A., Fundamentals of Power Electronics with MATLAB, Laxmi Publications, 2013.
  • 36. Nacar Cikan N., Cikan M., Reconfiguration of 123-bus unbalanced power distribution network analysis by considering minimization of current & voltage unbalanced indexes and power loss, International Journal of Electrical Power & Energy Systems, 157, 109796, 2024.
  • 37. Cikan M., Nacar Cikan N., Optimum allocation of multiple type and number of DG units based on IEEE 123-bus unbalanced multi-phase power distribution system, International Journal of Electrical Power and Energy Systems, 144, 108564, 2022.
  • 38. Cikan M., Kekezoglu B., Comparison of metaheuristic optimization techniques including Equilibrium optimizer algorithm in power distribution network reconfiguration, Alexandria Engineering Journal, 61 (2), 991–1031, 2022.

Year 2025, Volume: 40 Issue: 1, 555 - 572

Murat Çıkan

https://doi.org/10.17341/gazimmfd.1183267

Abstract

References

  • 1. Alkan S., Ates Y., Pilot Scheme Conceptual Analysis of Rooftop East–West-Oriented Solar Energy System with Optimizer, Energies (Basel), 16 (5), 2396, 2023.
  • 2. Gosumbonggot J., Nguyen D.-D., Fujita G., Partial Shading and Global Maximum Power Point Detections Enhancing MPPT for Photovoltaic Systems Operated in Shading Condition, 53rd International Universities Power Engineering Conference (UPEC), Glasgow, UK, 1–6, 2018.
  • 3. Ishaque K., Salam Z., Amjad M., Mekhilef S., An Improved Particle Swarm Optimization (PSO)–Based MPPT for PV With Reduced Steady-State Oscillation, IEEE Transactions on Power Electronics, 27 (8), 3627–3638, 2012.
  • 4. Rezk H., A comprehensive sizing methodology for stand-alone battery-less photovoltaic water pumping system under the Egyptian climate, Cogent Engineering, 3 (1), 1-12, 2016.
  • 5. Rezk H., Dousoky G. M., Technical and economic analysis of different configurations of stand-alone hybrid renewable power systems – A case study, Renewable and Sustainable Energy Reviews, 62, 941–953, 2016.
  • 6. Aygül K., Cikan M., Demirdelen T., Tumay M., Butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 45 (3), 1–19, 2019.
  • 7. Ponkarthik N., Kalidasa Murugavel K., Performance enhancement of solar photovoltaic system using novel Maximum Power Point Tracking, International Journal of Electrical Power & Energy Systems, 60, 1–5, 2014.
  • 8. Ramli M. Z., Salam Z., Analysis and experimental validation of partial shading mitigation in photovoltaic system using integrated DC-DC converter with maximum power point tracker, IET Renewable Power Generation, 13 (13), 2356–2366, 2019.
  • 9. Liu Y.-H., Huang S.-C., Huang J.-W., Liang W.-C., A Particle Swarm Optimization-Based Maximum Power Point Tracking Algorithm for PV Systems Operating Under Partially Shaded Conditions, IEEE Transactions on Energy Conversion, 27 (4), 1027–1035, 2012.
  • 10. Xiao W., Dunford W. G., A modified adaptive hill climbing MPPT method for photovoltaic power systems, IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551), Aachen, Germany, 1957-1963, 2004.
  • 11. Üzmuş H., Genç N., Çelik M. A., DSP based hybrid control method for PV systems, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (4), 2251–2260, 2023.
  • 12. Liu F., Duan S., Liu F., Liu B., Kang Y., A Variable Step Size INC MPPT Method for PV Systems, IEEE Transactions on Industrial Electronics, 55 (7), 2622–2628, 2008.
  • 13. Safari A., Mekhilef S., Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter, IEEE Transactions on Industrial Electronics, 58 (4), 1154–1161, 2011.
  • 14. Mei Q., Shan M., Liu L., Guerrero J. M., A Novel Improved Variable Step-Size Incremental-Resistance MPPT Method for PV Systems, IEEE Transactions on Industrial Electronics, 58 (6), 2427–2434, 2011.
  • 15. Kimball J. W., Krein P. T., Discrete-Time Ripple Correlation Control for Maximum Power Point Tracking, IEEE Transactions on Power Electronics, 23 (5), 2353–2362, 2008.
  • 16. Chen K., Tian S., Cheng Y., Bai L., An Improved MPPT Controller for Photovoltaic System Under Partial Shading Condition, IEEE Transactions on Sustainable Energy, 5 (3), 978–985, 2014.
  • 17. Thakkar N., Cormode D., A. Lonij V. P., Pulver S., Cronin A. D., A simple non-linear model for the effect of partial shade on PV systems, 35th IEEE Photovoltaic Specialists Conference, Honolulu, HI, USA, 2321–2326, 2010.
  • 18. Refaat A., Khalifa A. E., Elsakka M. M., Elhenawy Y., Kalas A., Elfar M. H., A novel metaheuristic MPPT technique based on enhanced autonomous group Particle Swarm Optimization Algorithm to track the GMPP under partial shading conditions - Experimental validation, Energy Conversion and Management, 287, 117124, 2023.
  • 19. Hamza Zafar M., Noman M.K., Mirza A.F., Mansoor M., Akhtar N., Qadir M.U., Khan N.A., Moosavi S.K.R., A novel meta-heuristic optimization algorithm based MPPT control technique for PV systems under complex partial shading condition, Sustainable Energy Technologies and Assessments, 47, 101367, 2021.
  • 20. Guo K., Cui L., Mao M., Zhou L., Zhang Q., An Improved Gray Wolf Optimizer MPPT Algorithm for PV System with BFBIC Converter Under Partial Shading, IEEE Access, 8, 103476–103490, 2020.
  • 21. Cikan M., Dogansahin K., A Comprehensive Evaluation of Up-to-Date Optimization Algorithms on MPPT Application for Photovoltaic Systems, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 45 (4), 10381–10407, October 2023.
  • 22. Dagal I., Akın B., Akboy E., MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink, Scintific Reports, 12 (1), 2664, 2022.
  • 23. Manna S., Singh D.K., Akella A.K., Kotb H., AboRas K.M., Zawbaa H.M., Kamel S., Design and implementation of a new adaptive MPPT controller for solar PV systems, Energy Reports, 9, 1818–1829, 2023.
  • 24. Karafil A., Comparison of the various irregular pulse density modulation (PDM) control pattern lengths for resonant converter with photovoltaic (PV) integration, Journal of the Faculty of Engineering and Architecture of Gazi University, 36 (3), 1595–1611, 2021.
  • 25. Akbari M. A., Zare M., Azizipanah-abarghooee R., Mirjalili S., Deriche M., The cheetah optimizer: a nature-inspired metaheuristic algorithm for large-scale optimization problems, Scientific Report, 12 (1), 10953, 2022.
  • 26. Mirjalili S., Mirjalili S. M., Lewis A., Grey Wolf Optimizer, Advances in Engineering Software, 69, 46–61, 2014.
  • 27. Mirjalili S., Hashim S. Z. M., A new hybrid PSOGSA algorithm for function optimization, International Conference on Computer and Information Application, Tianjin, China, 374–377, 2010.
  • 28. De Soto W., Klein S. A., Beckman W. A., Improvement and validation of a model for photovoltaic array performance, Solar Energy, 80(1), 78–88, 2006.
  • 29. Tian H., Mancilla-david F., Ellis K., Jenkins P., Muljadi E., A Detailed Performance Model for Photovoltaic Systems Preprint, Solar Energy Journal, 2012.
  • 30. Hejri M., Mokhtari H., Azizian M. R., Söder L., An analytical-numerical approach for parameter determination of a five-parameter single-diode model of photovoltaic cells and modules, International Journal of Sustainable Energy, 35 (4), 396–410, 2016.
  • 31. Ioinovici A., Modeling DC-DC Converters, Power Electronics and Energy Conversion Systems, 161–368, 2013.
  • 32. Ayop R., Tan C. W., Design of boost converter based on maximum power point resistance for photovoltaic applications, Solar Energy, 160, 322–335, 2017.
  • 33. Kyocera, High-efficiency multi-crystal photovoltaic module KC200GT, PV datasheet, 2, 2009.
  • 34. Seyedmahmoudian M., Mekhilef S., Rahmani R., Yusof R., Renani E. T., Analytical Modeling of Partially Shaded Photovoltaic Systems, Energies, 6 (1), 128–144, 2013.
  • 35. Shaffer R. A., Fundamentals of Power Electronics with MATLAB, Laxmi Publications, 2013.
  • 36. Nacar Cikan N., Cikan M., Reconfiguration of 123-bus unbalanced power distribution network analysis by considering minimization of current & voltage unbalanced indexes and power loss, International Journal of Electrical Power & Energy Systems, 157, 109796, 2024.
  • 37. Cikan M., Nacar Cikan N., Optimum allocation of multiple type and number of DG units based on IEEE 123-bus unbalanced multi-phase power distribution system, International Journal of Electrical Power and Energy Systems, 144, 108564, 2022.
  • 38. Cikan M., Kekezoglu B., Comparison of metaheuristic optimization techniques including Equilibrium optimizer algorithm in power distribution network reconfiguration, Alexandria Engineering Journal, 61 (2), 991–1031, 2022.
There are 38 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Makaleler
Authors

Murat Çıkan 0000-0001-6723-5769

Early Pub Date July 22, 2024
Publication Date
Submission Date October 2, 2022
Acceptance Date November 1, 2023
Published in Issue Year 2025 Volume: 40 Issue: 1

Cite

APA Çıkan, M. (2024). Çita optimizasyon algoritması kullanarak kısmi gölgelenme altındaki fotovoltaik sistemlerde maksimum güç noktası izleyicisinin tasarlanması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 40(1), 555-572. https://doi.org/10.17341/gazimmfd.1183267
AMA Çıkan M. Çita optimizasyon algoritması kullanarak kısmi gölgelenme altındaki fotovoltaik sistemlerde maksimum güç noktası izleyicisinin tasarlanması. GUMMFD. July 2024;40(1):555-572. doi:10.17341/gazimmfd.1183267
Chicago Çıkan, Murat. “Çita Optimizasyon Algoritması Kullanarak kısmi gölgelenme altındaki Fotovoltaik Sistemlerde Maksimum güç Noktası Izleyicisinin Tasarlanması”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40, no. 1 (July 2024): 555-72. https://doi.org/10.17341/gazimmfd.1183267.
EndNote Çıkan M (July 1, 2024) Çita optimizasyon algoritması kullanarak kısmi gölgelenme altındaki fotovoltaik sistemlerde maksimum güç noktası izleyicisinin tasarlanması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40 1 555–572.
IEEE M. Çıkan, “Çita optimizasyon algoritması kullanarak kısmi gölgelenme altındaki fotovoltaik sistemlerde maksimum güç noktası izleyicisinin tasarlanması”, GUMMFD, vol. 40, no. 1, pp. 555–572, 2024, doi: 10.17341/gazimmfd.1183267.
ISNAD Çıkan, Murat. “Çita Optimizasyon Algoritması Kullanarak kısmi gölgelenme altındaki Fotovoltaik Sistemlerde Maksimum güç Noktası Izleyicisinin Tasarlanması”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40/1 (July 2024), 555-572. https://doi.org/10.17341/gazimmfd.1183267.
JAMA Çıkan M. Çita optimizasyon algoritması kullanarak kısmi gölgelenme altındaki fotovoltaik sistemlerde maksimum güç noktası izleyicisinin tasarlanması. GUMMFD. 2024;40:555–572.
MLA Çıkan, Murat. “Çita Optimizasyon Algoritması Kullanarak kısmi gölgelenme altındaki Fotovoltaik Sistemlerde Maksimum güç Noktası Izleyicisinin Tasarlanması”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 40, no. 1, 2024, pp. 555-72, doi:10.17341/gazimmfd.1183267.
Vancouver Çıkan M. Çita optimizasyon algoritması kullanarak kısmi gölgelenme altındaki fotovoltaik sistemlerde maksimum güç noktası izleyicisinin tasarlanması. GUMMFD. 2024;40(1):555-72.