Comparison of Maximum Power Point Tracking Techniques on Photovoltaic Panels

Yıl 2020, Cilt: 6 Sayı: 1, 14 - 29, 22.05.2020

Evren İşen , Akif Şengül

https://doi.org/10.28979/comufbed.686721

Cited By: 1

Öz

In this study, a simulation is performed in Matlab/Simulink to evaluate the energy production performance of the perturb & observe, incremental conductance, short circuit current and open circuit voltage techniques. In order to evaluate the performance of the techniques, they are tested under constant temperature and irradiation conditions, as well as variable temperature and irradiation conditions. In the study, 1Soltech 1STH-215-P model photovoltaic panel is used. The maximum power point tracking is applied with a DC-DC boost converter, and the energy is stored in the battery. Maximum power point tracking algorithms are applied with m-file code using Matlab Function block in Simulink. The m-file codes, the extracted power waveforms and the amount of produced energy are presented in the study. It is observed that the energy performance of the short circuit current and open circuit voltage techniques varies depending on the measurement period, especially in variable weather conditions, while the perturb & observe and the incremental conductance algorithms are the ones that produce the most energy. While the open circuit voltage technique produces more energy than the short circuit current at constant temperature and variable irradiation, the short circuit current algorithm at constant irradiation and variable temperature produces more energy. While two sensors are used for current and voltage measurement in perturb & observe and incremental conductance techniques, the use of a single sensor in short circuit current and open circuit voltage techniques and the simplicity of the algorithms are seen as the advantageous aspects of these techniques. 

Anahtar Kelimeler

fotovoltaik panel, güç elektroniği, maksimum güç noktası, mppt, güneş enerjisi

Kaynakça

• Ahmed, J., & Salam, Z. (2015). An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency. Applied Energy, 150, 97-108.
• Alsumiri, M. (2019). Residual Incremental Conductance Based Nonparametric MPPT Control for Solar Photovoltaic Energy Conversion System. IEEE Access, 7, 87901-87906.
• Hasan, M., & Parida, S. (2016). An overview of solar photovoltaic panel modeling based on analytical and experimental viewpoint. Renewable and Sustainable Energy Reviews, 75-83.
• Huynh, D. C. (2014). An Improved Incremental Conductance Maximum Power Point Tracking Algorithm for Solar Photovoltaic Panels. International Journal of Science and Research, 3(10), 342-347.
• Irfan, M., Zhao, Z.-y., Ahmad, M., & Rehman, A. (2019). A Techno-Economic Analysis of Off-Grid Solar PV System: A Case Study for Punjab Province in Pakistan. Processes, 1-14.
• Jager-Waldau, A. (2019). JRC Science For Policy Report, PV Status Report 2019. Ispra: European Commission.
• Karami, N., Moubayed, N., & Outbib, R. (2017). General review and classification of different MPPT Techniques. Renewable and Sustainable Energy Reviews, 1-18.
• Kharrazi, A., Sreeram, V., & Mishra, Y. (2020). Assessment techniques of the impact of grid-tied rooftop photovoltaic generation on the power quality of low voltage distribution network - A review. Renewable and Sustainable Energy Reviews, 1-16.
• Kollimalla, S. K., & Mishra, M. K. (2014). Variable Perturbation Size Adaptive P&O MPPT Algorithm for Sudden Changes in Irradiance. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 718-728.
• Kumari, J. S., Babu, C. S., & Kullayappa, T. R. (2011). Design and Analysis of Open Circuit Voltage Based Maximum Power Point Tracking for Photovoltaic System. International Journal of Advances in Science and Technology, 2(2), 51-60.
• Mei, Q., Shan, M., Liu, L., & Guerrero, J. M. (2011). A Novel Improved Variable Step-SizeIncremental-Resistance MPPTMethod for PV Systems. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 58(6), 2427-2434.
• Mensah, L. D., Yamoah, J. O., & Adaramola, M. S. (2019). Performance evaluation of a utility-scale grid-tied solar photovoltaic (PV) installation in Ghana. Energy for Sustainable Development, 82-87.
• Moghbelli, H., Ellithy, K., Eslami, Z., Vartanian, R., Wannous, D., Ghamrawy, A. E., Nicola, S. (2009). Investigation of Solar Energy Applications with Design and Implementation of Photovoltaic Traffic Light Signal System for Qatar. International Conference on Renewable Energies and Power Quality, (s. 1-8). Valencia.
• Pilakkat, D., & Kanthalakshmi, S. (2019). An improved P&O algorithm integrated with artificial bee colony for photovoltaic systems under partial shading conditions. Solar Energy, 178, 37-47.
• Punitha, K., Devaraj, D., & Sakthivel, S. (2013). Development and analysis of adaptive fuzzy controllers for photovoltaic system under varying atmospheric and partial shading condition. Applied Soft Computing, 13, 4320-4332.
• Rawat, R., Kaushik, S., & Lamba, R. (2016). A review onmodeling, design methodology and size optimization of photovoltaic based water pumping,standalone and grid connected system. Renewable and Sustainable Energy Reviews, 1506-1519.
• Sontake, V. C., & Kalamkar, V. R. (2016). Solar photovoltaic water pumping system - A comprehensive review. Renewable and Sustainable Energy Reviews, 59, 1038-1067.
• Subudhi, B., & Pradhan, R. (2011). Characteristics Evaluation and Parameter Extraction of a Solar Array based on Experimental Analysis. IEEE PEDS, (s. 340-344). Singapore. Xue, J. (2017). Photovoltaic agriculture - New opportunity for photovoltaic applications in China. Renewable and Sustainable Energy Reviews, 73, 1-9.
• Zainuri, M. A., Radzi, M. A., Soh, A. C., & Rahim, N. A. (2014). Development of adaptive perturb and observe-fuzzy control maximum power point tracking forphotovoltaic boost dc–dc converter. IET Renewable Power Generation, 8(2), 183-194.
• Zakzouk, N. E., Elsaharty, M. A., Abdelsalam, A. K., Helal, A. A., & Williams, B. W. (2015). Improved performance low-cost incrementalconductance PV MPPT technique. IET Renewable Power Generation, 10(4), 561-574.