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Değişen Çevresel Koşullar İçin Üç MGNT Algoritmasının Deneysel Doğrulaması ve Karşılaştırmalı Analizi

Yıl 2021, , 17 - 34, 15.12.2021
https://doi.org/10.31590/ejosat.1005041

Öz

Bu çalışma ile güneş dizi simülatörü (Solar Array Simulator, SAS) aracılığıyla oluşturulan üç farklı ortamda; değiştir ve gözle (Perturb and Observe, P&O), artımlı iletkenlik (Incremental Conductance, IC) ve bulanık mantık denetleyicisi (Fuzzy Logic Controller, FLC) tekniklerini temel alan maksimum güç noktası takibi (Maksimum Power Point Tracking, MPPT) algoritmalarının uygulamalı olarak performans analizleri yapılmıştır. Bu amaca yönelik olarak BK Precision firmasının güneş dizi simülatörü üzerinden sıcaklık (T) ve güneş ışımasının (G) zamana göre değişim gösterdiği 3 farklı ortam senaryosu oluşturulmuştur. Belirtilen MGNT algoritmaları bu ortamlarda ayrı ayrı çalıştırılarak performans analizleri yapılmıştır. Çalışma kapsamında yük olarak 500 W’lık omik yük (serpantinli rezistans) kullanılmış ve güneş dizi simülatöründen yüke olan güç aktarımı DA-DA (Doğru Akım, DA) yükselten (Boost, step-up) dönüştürücü üzerinden yapılmıştır. Dönüştürücünün kontrolü ve bahsedilen algoritmaların işletilmesi SMT firmasının geliştirme kartı olan Nucleo 32F103RB üzerinden yapılmış ve elde edilen sonuçlar tartışılmıştır.

Kaynakça

  • Ali, M. N., Mahmoud, K., Lehtonen, M., & Darwish, M. M. (2021). An efficient fuzzy-logic based variable-step incremental conductance MPPT method for grid-connected PV systems. Ieee Access, 9, 26420-26430.
  • Abouelela, M. (2020). Power Electronics for practical implementation of PV MPPT. In Modern Maximum Power Point Tracking Techniques for Photovoltaic Energy Systems (pp. 65-105). Springer, Cham.
  • AKBOY, E. Modelling and Control of A High Power Factor Grid Connected PV Sytem Under Varying Irraditions. Avrupa Bilim ve Teknoloji Dergisi, (17), 794-802.
  • Alsumiri, M. (2019). Residual incremental conductance based nonparametric MPPT control for solar photovoltaic energy conversion system. IEEE Access, 7, 87901-87906.
  • Ammar, H. H., Azar, A. T., Shalaby, R., & Mahmoud, M. I. (2019). Metaheuristic optimization of fractional order incremental conductance (FO-INC) maximum power point tracking (MPPT). Complexity, 2019.
  • Belkaid, A., Colak, I., & Kayisli, K. (2017). Implementation of a modified P&O-MPPT algorithm adapted for varying solar radiation conditions. Electrical Engineering, 99(3), 839-846.
  • Bhattacharyya, S., Samanta, S., & Mishra, S. (2020). Steady Output and Fast Tracking MPPT (SOFT-MPPT) for P&O and InC Algorithms. IEEE Transactions on Sustainable Energy, 12(1), 293-302.
  • da Rocha, N. M. M., Brighenti, L. L., Passos, J. C., & Martins, D. C. (2019). Photovoltaic Cell Cooling as a Facilitator for MPPT. IEEE Latin America Transactions, 17(10), 1569-1577.
  • Gökkuş, G., (2020). Meteorolojik Verileri Kullanan Mppt Kontrollü Rüzgar-Güneş Hibrit Enerji Sistemi Tasarımı Ve Uygulaması, (Doktora Tezi). Konya Teknik Üniversitesi, Konya.
  • Gouabi, H., Hazzab, A., Habbab, M., Rezkallah, M., & Chandra, A. (2021). Experimental implementation of a novel scheduling algorithm for adaptive and modified P&O MPPT controller using fuzzy logic for WECS. International Journal of Adaptive Control and Signal Processing.
  • Harrag, A., & Messalti, S. (2018). How fuzzy logic can improve PEM fuel cell MPPT performances?. International Journal of Hydrogen Energy, 43(1), 537-550.
  • Iftikhar, R., Ahmad, I., Arsalan, M., Naz, N., Ali, N., & Armghan, H. (2018). MPPT for photovoltaic system using nonlinear controller. International Journal of Photoenergy, 2018.
  • Ilyas, A., Ayyub, M., Khan, M. R., Jain, A., & Husain, M. A. (2018). Realisation of incremental conductance the MPPT algorithm for a solar photovoltaic system. International Journal of Ambient Energy, 39(8), 873-884.
  • Kandemir, E., Borekci, S., & Cetin, N. S. (2018). Comparative Analysis of Reduced-Rule Compressed Fuzzy Logic Control and Incremental Conductance MPPT Methods. Journal of Electronic Materials, 47(8).
  • Kulaksiz, A. A., ALHAJOMAR, F., & GOKKUS, G. (2019). Rapid Control Prototyping based on 32-Bit ARM Cortex-M3 Microcontroller for Photovoltaic MPPT Algorithms. International Journal of Renewable Energy Research (IJRER), 9(4), 1938-1947.
  • Kwan, T. H., & Wu, X. (2017). High performance P&O based lock-on mechanism MPPT algorithm with smooth tracking. Solar Energy, 155, 816-828.
  • Li, S. (2019). A variable-weather-parameter MPPT control strategy based on MPPT constraint conditions of PV system with inverter. Energy Conversion and Management, 197, 111873.
  • Liu, L., Huang, C., Mu, J., Cheng, J., & Zhu, Z. (2019). A P&O MPPT with a novel analog power-detector for WSNs applications. IEEE Transactions on Circuits and Systems II: Express Briefs, 67(10), 1680-1684.
  • Mousa, H. H., Youssef, A. R., & Mohamed, E. E. (2020). Hybrid and adaptive sectors P&O MPPT algorithm based wind generation system. Renewable Energy, 145, 1412-1429.
  • Necaibia, S., Kelaiaia, M. S., Labar, H., & Necaibia, A. (2017). Implementation of an improved incremental conductance MPPT control based boost converter in photovoltaic applications. International Journal of Emerging Electric Power Systems, 18(4).
  • Ochab, P., Kokoszka, W., Kogut, J., Skrzypczak, I., Szyszka, J., & Starakiewicz, A. (2017, December). Passive Residential Houses with the Accumulation Properties of Ground as a Heat Storage Medium. In IOP Conference Series: Earth and Environmental Science (Vol. 95, No. 4, p. 042017). IOP Publishing.
  • Omar, F. A., Gökkuş, G., & Kulaksız, A. A. (2019). Şebekeden Bağımsız FV Sistemde Maksimum Güç Noktası Takip Algoritmalarının Değişken Hava Şartları Altında Karşılaştırmalı Analizi. Konya Mühendislik Bilimleri Dergisi, 7(3), 585-594.
  • Ram, J. P., Rajasekar, N., & Miyatake, M. (2017). Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review. Renewable and Sustainable Energy Reviews, 73, 1138-1159.
  • Rezk, H., Aly, M., Al-Dhaifallah, M., & Shoyama, M. (2019). Design and hardware implementation of new adaptive fuzzy logic-based MPPT control method for photovoltaic applications. Ieee Access, 7, 106427-106438.
  • Robles Algarín, C., Taborda Giraldo, J., & Rodriguez Alvarez, O. (2017). Fuzzy logic based MPPT controller for a PV system. Energies, 10(12), 2036.
  • Sahoo, J., Samanta, S., & Bhattacharyya, S. (2020). Adaptive PID controller with P&O MPPT algorithm for photovoltaic system. IETE Journal of Research, 66(4), 442-453.
  • Sener, E., Turk, I., Yazar, I., & Karakoç, T. H. (2019). Solar powered UAV model on MATLAB/Simulink using incremental conductance MPPT technique. Aircraft Engineering and Aerospace Technology.
  • Shengqing, L., Fujun, L., Jian, Z., Wen, C., & Donghui, Z. (2020). An improved MPPT control strategy based on incremental conductance method. Soft Computing, 24(8), 6039-6046.
  • Shang, L., Guo, H., & Zhu, W. (2020). An improved MPPT control strategy based on incremental conductance algorithm. Protection and Control of Modern Power Systems, 5(1), 1-8.
  • Sundararaj, V., Anoop, V., Dixit, P., Arjaria, A., Chourasia, U., Bhambri, P., ... & Sundararaj, R. (2020). CCGPA‐MPPT: Cauchy preferential crossover‐based global pollination algorithm for MPPT in photovoltaic system. Progress in Photovoltaics: Research and Applications, 28(11), 1128-1145.
  • Talbi, B., Krim, F., Rekioua, T., Laib, A., & Feroura, H. (2017). Design and hardware validation of modified P&O algorithm by fuzzy logic approach based on model predictive control for MPPT of PV systems. Journal of Renewable and Sustainable Energy, 9(4), 043503.
  • Tawanna, N., Takkabutr, F., Kesutha, A., & Wongsathan, R. (2020). MAXIMIZING EFFICIENCY OF A PHOTOVOLTAIC WATER PUMPING SYSTEM USING THE MPPTBASED FUZZY LOGIC CONTROLLER. Suranaree Journal of Science & Technology, 27(4).
  • Tang, S., Sun, Y., Chen, Y., Zhao, Y., Yang, Y., & Szeto, W. (2017). An enhanced MPPT method combining fractional-order and fuzzy logic control. IEEE Journal of Photovoltaics, 7(2), 640-650.
  • Verma, P., Garg, R., & Mahajan, P. (2020). Asymmetrical interval type-2 fuzzy logic control based MPPT tuning for PV system under partial shading condition. ISA transactions, 100, 251-263.
  • Wellawatta, T. R., Seo, Y. T., Lee, H. H., & Choi, S. J. (2017, October). A regulated incremental conductance (r-INC) MPPT algorithm for photovoltaic system. In 2017 IEEE Energy Conversion Congress and Exposition (ECCE) (pp. 2305-2309). IEEE.
  • YARIKKAYA, S., & Vardar, K. (2020). Rapid Prototype Development of Single Phase Grid Connected PV Inverter Using Stm32f4 and Matlab. Avrupa Bilim ve Teknoloji Dergisi, (18), 213-223.
  • Yiğit, S., & YAĞCI, M. (2020). Modelling of Maximum Power Point Tracking of Photovoltaic Module Using Incremental Conductance Method. Avrupa Bilim ve Teknoloji Dergisi, 1-5.
  • Yin, L., Yu, S., Zhang, X., & Tang, Y. (2017). Simple adaptive incremental conductance MPPT algorithm using improved control model. Journal of Renewable and Sustainable Energy, 9(6), 065501.

Experimental Verification And Comparative Analysis Of Three MPPT Algorithms For Varying Environmental Conditions

Yıl 2021, , 17 - 34, 15.12.2021
https://doi.org/10.31590/ejosat.1005041

Öz

In this study, in 3 different environments created by solar array simulator (SAS); Performance analyzes of maximum power point tracking (MPPT) algorithms based on Perturb & Observe (P&O), Incremental Conductance (IC) and Fuzzy Logic Controller (FLC) techniques have been carried out. For this purpose, 3 different environment scenarios in which temperature (T) and solar radiation (G) change according to time were created on the solar array simulator of BK Precision company. Performance analyzes were made by running the specified MPPT algorithms separately in these environments. Within the scope of the study, a 500 W ohmic load was used and the power transfer from the solar array simulator to the load was made via the DC-DC Boost converter. The control of the converter and the operation of the mentioned algorithms were made on the Nucleo 32F103RB, the development board of SMT company, and the results were discussed.

Kaynakça

  • Ali, M. N., Mahmoud, K., Lehtonen, M., & Darwish, M. M. (2021). An efficient fuzzy-logic based variable-step incremental conductance MPPT method for grid-connected PV systems. Ieee Access, 9, 26420-26430.
  • Abouelela, M. (2020). Power Electronics for practical implementation of PV MPPT. In Modern Maximum Power Point Tracking Techniques for Photovoltaic Energy Systems (pp. 65-105). Springer, Cham.
  • AKBOY, E. Modelling and Control of A High Power Factor Grid Connected PV Sytem Under Varying Irraditions. Avrupa Bilim ve Teknoloji Dergisi, (17), 794-802.
  • Alsumiri, M. (2019). Residual incremental conductance based nonparametric MPPT control for solar photovoltaic energy conversion system. IEEE Access, 7, 87901-87906.
  • Ammar, H. H., Azar, A. T., Shalaby, R., & Mahmoud, M. I. (2019). Metaheuristic optimization of fractional order incremental conductance (FO-INC) maximum power point tracking (MPPT). Complexity, 2019.
  • Belkaid, A., Colak, I., & Kayisli, K. (2017). Implementation of a modified P&O-MPPT algorithm adapted for varying solar radiation conditions. Electrical Engineering, 99(3), 839-846.
  • Bhattacharyya, S., Samanta, S., & Mishra, S. (2020). Steady Output and Fast Tracking MPPT (SOFT-MPPT) for P&O and InC Algorithms. IEEE Transactions on Sustainable Energy, 12(1), 293-302.
  • da Rocha, N. M. M., Brighenti, L. L., Passos, J. C., & Martins, D. C. (2019). Photovoltaic Cell Cooling as a Facilitator for MPPT. IEEE Latin America Transactions, 17(10), 1569-1577.
  • Gökkuş, G., (2020). Meteorolojik Verileri Kullanan Mppt Kontrollü Rüzgar-Güneş Hibrit Enerji Sistemi Tasarımı Ve Uygulaması, (Doktora Tezi). Konya Teknik Üniversitesi, Konya.
  • Gouabi, H., Hazzab, A., Habbab, M., Rezkallah, M., & Chandra, A. (2021). Experimental implementation of a novel scheduling algorithm for adaptive and modified P&O MPPT controller using fuzzy logic for WECS. International Journal of Adaptive Control and Signal Processing.
  • Harrag, A., & Messalti, S. (2018). How fuzzy logic can improve PEM fuel cell MPPT performances?. International Journal of Hydrogen Energy, 43(1), 537-550.
  • Iftikhar, R., Ahmad, I., Arsalan, M., Naz, N., Ali, N., & Armghan, H. (2018). MPPT for photovoltaic system using nonlinear controller. International Journal of Photoenergy, 2018.
  • Ilyas, A., Ayyub, M., Khan, M. R., Jain, A., & Husain, M. A. (2018). Realisation of incremental conductance the MPPT algorithm for a solar photovoltaic system. International Journal of Ambient Energy, 39(8), 873-884.
  • Kandemir, E., Borekci, S., & Cetin, N. S. (2018). Comparative Analysis of Reduced-Rule Compressed Fuzzy Logic Control and Incremental Conductance MPPT Methods. Journal of Electronic Materials, 47(8).
  • Kulaksiz, A. A., ALHAJOMAR, F., & GOKKUS, G. (2019). Rapid Control Prototyping based on 32-Bit ARM Cortex-M3 Microcontroller for Photovoltaic MPPT Algorithms. International Journal of Renewable Energy Research (IJRER), 9(4), 1938-1947.
  • Kwan, T. H., & Wu, X. (2017). High performance P&O based lock-on mechanism MPPT algorithm with smooth tracking. Solar Energy, 155, 816-828.
  • Li, S. (2019). A variable-weather-parameter MPPT control strategy based on MPPT constraint conditions of PV system with inverter. Energy Conversion and Management, 197, 111873.
  • Liu, L., Huang, C., Mu, J., Cheng, J., & Zhu, Z. (2019). A P&O MPPT with a novel analog power-detector for WSNs applications. IEEE Transactions on Circuits and Systems II: Express Briefs, 67(10), 1680-1684.
  • Mousa, H. H., Youssef, A. R., & Mohamed, E. E. (2020). Hybrid and adaptive sectors P&O MPPT algorithm based wind generation system. Renewable Energy, 145, 1412-1429.
  • Necaibia, S., Kelaiaia, M. S., Labar, H., & Necaibia, A. (2017). Implementation of an improved incremental conductance MPPT control based boost converter in photovoltaic applications. International Journal of Emerging Electric Power Systems, 18(4).
  • Ochab, P., Kokoszka, W., Kogut, J., Skrzypczak, I., Szyszka, J., & Starakiewicz, A. (2017, December). Passive Residential Houses with the Accumulation Properties of Ground as a Heat Storage Medium. In IOP Conference Series: Earth and Environmental Science (Vol. 95, No. 4, p. 042017). IOP Publishing.
  • Omar, F. A., Gökkuş, G., & Kulaksız, A. A. (2019). Şebekeden Bağımsız FV Sistemde Maksimum Güç Noktası Takip Algoritmalarının Değişken Hava Şartları Altında Karşılaştırmalı Analizi. Konya Mühendislik Bilimleri Dergisi, 7(3), 585-594.
  • Ram, J. P., Rajasekar, N., & Miyatake, M. (2017). Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review. Renewable and Sustainable Energy Reviews, 73, 1138-1159.
  • Rezk, H., Aly, M., Al-Dhaifallah, M., & Shoyama, M. (2019). Design and hardware implementation of new adaptive fuzzy logic-based MPPT control method for photovoltaic applications. Ieee Access, 7, 106427-106438.
  • Robles Algarín, C., Taborda Giraldo, J., & Rodriguez Alvarez, O. (2017). Fuzzy logic based MPPT controller for a PV system. Energies, 10(12), 2036.
  • Sahoo, J., Samanta, S., & Bhattacharyya, S. (2020). Adaptive PID controller with P&O MPPT algorithm for photovoltaic system. IETE Journal of Research, 66(4), 442-453.
  • Sener, E., Turk, I., Yazar, I., & Karakoç, T. H. (2019). Solar powered UAV model on MATLAB/Simulink using incremental conductance MPPT technique. Aircraft Engineering and Aerospace Technology.
  • Shengqing, L., Fujun, L., Jian, Z., Wen, C., & Donghui, Z. (2020). An improved MPPT control strategy based on incremental conductance method. Soft Computing, 24(8), 6039-6046.
  • Shang, L., Guo, H., & Zhu, W. (2020). An improved MPPT control strategy based on incremental conductance algorithm. Protection and Control of Modern Power Systems, 5(1), 1-8.
  • Sundararaj, V., Anoop, V., Dixit, P., Arjaria, A., Chourasia, U., Bhambri, P., ... & Sundararaj, R. (2020). CCGPA‐MPPT: Cauchy preferential crossover‐based global pollination algorithm for MPPT in photovoltaic system. Progress in Photovoltaics: Research and Applications, 28(11), 1128-1145.
  • Talbi, B., Krim, F., Rekioua, T., Laib, A., & Feroura, H. (2017). Design and hardware validation of modified P&O algorithm by fuzzy logic approach based on model predictive control for MPPT of PV systems. Journal of Renewable and Sustainable Energy, 9(4), 043503.
  • Tawanna, N., Takkabutr, F., Kesutha, A., & Wongsathan, R. (2020). MAXIMIZING EFFICIENCY OF A PHOTOVOLTAIC WATER PUMPING SYSTEM USING THE MPPTBASED FUZZY LOGIC CONTROLLER. Suranaree Journal of Science & Technology, 27(4).
  • Tang, S., Sun, Y., Chen, Y., Zhao, Y., Yang, Y., & Szeto, W. (2017). An enhanced MPPT method combining fractional-order and fuzzy logic control. IEEE Journal of Photovoltaics, 7(2), 640-650.
  • Verma, P., Garg, R., & Mahajan, P. (2020). Asymmetrical interval type-2 fuzzy logic control based MPPT tuning for PV system under partial shading condition. ISA transactions, 100, 251-263.
  • Wellawatta, T. R., Seo, Y. T., Lee, H. H., & Choi, S. J. (2017, October). A regulated incremental conductance (r-INC) MPPT algorithm for photovoltaic system. In 2017 IEEE Energy Conversion Congress and Exposition (ECCE) (pp. 2305-2309). IEEE.
  • YARIKKAYA, S., & Vardar, K. (2020). Rapid Prototype Development of Single Phase Grid Connected PV Inverter Using Stm32f4 and Matlab. Avrupa Bilim ve Teknoloji Dergisi, (18), 213-223.
  • Yiğit, S., & YAĞCI, M. (2020). Modelling of Maximum Power Point Tracking of Photovoltaic Module Using Incremental Conductance Method. Avrupa Bilim ve Teknoloji Dergisi, 1-5.
  • Yin, L., Yu, S., Zhang, X., & Tang, Y. (2017). Simple adaptive incremental conductance MPPT algorithm using improved control model. Journal of Renewable and Sustainable Energy, 9(6), 065501.
Toplam 38 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Göksel Gökkuş 0000-0003-4266-5556

Ahmet Afşin Kulaksız 0000-0003-3216-8185

Yayımlanma Tarihi 15 Aralık 2021
Yayımlandığı Sayı Yıl 2021

Kaynak Göster

APA Gökkuş, G., & Kulaksız, A. A. (2021). Değişen Çevresel Koşullar İçin Üç MGNT Algoritmasının Deneysel Doğrulaması ve Karşılaştırmalı Analizi. Avrupa Bilim Ve Teknoloji Dergisi(30), 17-34. https://doi.org/10.31590/ejosat.1005041