Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation
Photovoltaic (PV) system is one of the reliable alternative sources of energy and its contribution in energy sector is growing rapidly. The performance of PV system depends upon the solar insolation, which will be varying throughout the day, season and year. The biggest challenge is to obtain the maximum power from PV array at varying insolation levels. The maximum power point tracking (MPPT) controller, in association with tracking algorithm will act as a principal element in driving the PV system at maximum power point (MPP). In this paper, the simulation model has been developed and the results were compared for perturb and observe, incremental conductance, extremum seeking control and fuzzy logic controller based MPPT algorithms at different irradiation levels on a 10 KW PV array. The results obtained were analysed in terms of convergence rate and their efficiency to track the MPP.
Article History: Received 3rd Oct 2016; Received in revised form 6th January 2017; Accepted 10th February 2017; Available online
How to Cite This Article: Naick, B. K., Chatterjee, T. K. & Chatterjee, K. (2017) Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation. Int Journal of Renewable Energy Development, 6(1), 65-74.
- 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.
- Bazzi, A. M. & Krein. P. T. (2011) Concerning “Maximum Power Point Tracking for Photovoltaic Optimization Using Ripple-Based Extremum Seeking Control”. IEEE Trans. on Power Electronics, 26 (6), 1611-1612.
- Bendib, B., Belmili, H. & Krim, F. (2015) A survey of the most used MPPT methods: Conventional and advanced algorithms applied for photovoltaic systems. Renewable and Sustainable Energy Reviews, 45, 637–648.
- Benyoucef, A. S., Chouder, A., Kara, K., Silvestrec, S. & saheda, O. A. (2015) Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions. Applied Soft Computing, 32, 38–48.
- Dileep, G. & Singh, S. N. (2015) Maximum power point tracking of solar photovoltaic system using modified perturbation and observation method. Renewable and Sustainable Energy Reviews, 50, 109–129.
- Elobaid, L. M., Abdelsalam, A. k. & Zakzouk, E. E. (2015) Artificial neural network-based photovoltaic maximum power point tracking techniques: a survey. IET Renewable power Generation, 9(8), 1043-1063.
- Eltawil, M. A. & Zhao, Z. (2013) MPPT techniques for photovoltaic applications. Renewable and Sustainable Energy Reviews, 25, 793–813.
- Fathy, A. (2015) Reliable and efficient approach for mitigating the shading effect on photovoltaic module based on Modified Artificial Bee Colony algorithm. Renewable Energy, 81, 78-88.
- Femia, N., Petrone, G., Spagnuolo, G. & Vitell, M. (2005) Optimization of Perturb and Observe Maximum Power Point Tracking Method. IEEE Trans. Power Electronics, 20(4), 963-973.
- Ghaffari, A., Krsti´c, M. & Seshagiri, S. (2014) Power Optimization for Photovoltaic Microconverters Using Multivariable Newton-Based Extremum Seeking. IEEE Trans. Control Systems Technology, 22 (6), 2141-2149.
- Ghaffari, A., Seshagiri, S. & Krstić, M (2015) Multivariable maximum power point tracking for photovoltaic micro-converters using extremum seeking. Control Engineering Practice, 35, 83–91.
- Guenounou, O., Dahhou, B. & Chabour, F. (2014) Adaptive fuzzy controller based MPPT for photovoltaic systems. Energy Conversion and Management, 78, 843–850.
- Jianga, L. L., Maskell, D.L. & Patra. J.C. (2013) A novel ant colony optimization-based maximum power point tracking for photovoltaic systems under partially shaded conditions. Energy and Buildings, 58, 227–236.
- Khateb, A. E., Rahim, N.A., Selvaraj, J. & Uddin, M.N. (2014) Fuzzy-Logic-Controller-Based SEPIC Converter for Maximum Power Point Tracking. IEEE Trans. Industry Applications, 50(4), 2349-2358.
- Kofinas, P., Dounis, A. I., Papadakis, G. & Assimakopoulos, M. N. (2015) An Intelligent MPPT controller based on direct neural control for partially shaded PV system. Energy and Buildings, 90, 51–64.
- Larbes, C., Aı¨t Cheikh, S, M., Obeidi, T. & Zerguerras, A. (2009) Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system. Renewable Energy, 34(10), 2093–2100.
- Leyva, R., Alonso, C., Queinnec, I., Cid-Pastor, A., Lagrange, D. & Martínez-Salamero, L. (2006) MPPT of Photovoltaic Systems using Extremum–Seeking Control. IEEE Trans. Aerospace and Electronic Systems, 42 (1), 249-258.
- Leyva, R., Olalla, C., Zazo, H., Cabal, C., Cid-Pastor, A., Queinnec, I. & Alonso, C. (2012) MPPT Based on Sinusoidal Extremum-Seeking Control in PV Generation. International Journal of Photoenergy, 2012(Article ID 672765), 7 pages.
- Li, X., Li, Y. & Seem, J. E. (2013) Maximum Power Point Tracking for Photovoltaic System Using Adaptive Extremum Seeking Control. IEEE Trans. Control Systems Technology, 21(6), 2315-2322.
- Lin, W., Hong, C. & Chen, C. (2011) Neural-Network-Based MPPT Control of a Stand-Alone Hybrid Power Generation System. IEEE Trans. Power Electronics, 26(12), 3571-3581.
- Liu, F., Duan, S., Liu, F., Liu, B. & Kang, Y. (2008) A Variable Step Size INC MPPT Method for PV Systems. IEEE Trans. Industrial Electronics, 55(7), 2622-2628.
- Liu, Y., Huang, S., Huang, J. & Liang, W. (2012) A Particle Swarm Optimization-Based Maximum Power Point Tracking Algorithm for PV Systems Operating Under Partially Shaded Conditions. IEEE Trans. Energy Conversion, 27(4), 1027-1035.
- Malek, H., Dadras, S. & Chen, Y. (2013) An Improved Maximum Power Point Tracking based on Fractional Order Extremum Seeking Control in Grid-Connected Photovoltaic (PV) Systems. proceedings of the ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC/CIE 2013, Portland, Oregon, USA, August 4-7, 2013.
- Mohanty, S., Subudhi, B. & Ray, P. K. (2016) A New MPPT Design Using Grey Wolf Optimization Technique for Photovoltaic System under Partial Shading Conditions. IEEE Trans. Sustainable Energy, 7(1), 181-188.
- Oliveira, F. M. D., Silva, S. A. O. D., Durand, F. R., Sampaio, L. P., Bacon, V. D. & Campanhol, L. B. G. (2016) Grid-tied photovoltaic system based on PSO MPPT technique with active power line conditioning. IET Power Electronics, 9(6), 1180-1191.
- Piegari, L. & Rizzo, R. (2010) Adaptive perturb and observe algorithm for photovoltaic maximum power point tracking. IET Renewable Power Generation, 4(4), 317– 328.
- Saravanan, S. & Babu, N. R. (2016) Maximum power point tracking algorithms for photovoltaic system – A review. Renewable and Sustainable Energy Reviews, 57, 192–204.
- Tey, K. S. & Mekhilef, S. (2014) Modified incremental conductance MPPT algorithm to mitigate inaccurate responses under fast-changing solar irradiation level. Solar Energy, 101, 333–342.
- Villalva, M. G., Gazoli, J. R. & Filho, E. R. (2009) Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays. IEEE Trans. Power Electronics, 24(5), 1198-1208.
- Zainuri, M. A. A. M., Radzi, M. A. M., Soh, A. C. & Rahim, N. A. (2014) Development of adaptive perturb and observe-fuzzy control maximum power point tracking for photovoltaic boost dc–dc converter. IET Renewable Power Generation, 8(2), 183–194.
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to International Journal of Renewable Energy Development and Center of Biomass and Renewable Energy, Department of Chemical Engineering Diponegoro University as publisher of the journal.
Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , will be allowed only with a written permission from International Journal of Renewable Energy Development and Center of Biomass and Renewable Energy, Department of Chemical Engineering Diponegoro University.
International Journal of Renewable Energy Development and Center of Biomass and Renewable Energy, Department of Chemical Engineering Diponegoro University, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in the International Journal of Renewable Energy Development are sole and exclusive responsibility of their respective authors and advertisers.