Fuzzy maximum power point tracking compared to sliding mode technique for photovoltaic systems based on DC-DC boost converter
DOI:
https://doi.org/10.20998/2074-272X.2021.1.10Keywords:
solar panel, maximum power point tracking, perturb and observe, sliding mode, Fuzzy logicAbstract
Aim. This paper presents the amelioration of maximum power point tracking using fuzzy logic methods for photovoltaic system supplying a standalone system. Method. The main role of the maximum power tracking is to force the system for working at the maximum point for each change of meteorological conditions. The classic technique Perturb and Observe is more attractive due to its simple and high efficiency. Sliding mode is a non-linear control technique; characterised by robustness against the parameters change or disturbances, it gives a good maximum power operation under different conditions such as changing solar radiation and photovoltaic cell temperature. Novelty. Fuzzy logic tracking technique is treated. Fuzzy rules construction is based on Perturb and Observe behaviour when the appropriate disturbance step is produced in order to obtain a fast system with an acceptable precision. We use in our study 60 W photovoltaic panel associated to boost chopper converter in order to supply a standalone system. Results. As show in results figures using fuzzy maximum power point tracking the ameliorate performances especially the very low oscillation rate (nearly 0.6 W), and very acceptable response time 0.1 s.
References
Weidong Xiao, Dunford W.G. A modified adaptive hill climbing MPPT method for photovoltaic power systems. 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551), Aachen, Germany, 2004, vol. 3, pp. 1957-1963. doi: https://doi.org/10.1109/pesc.2004.1355417.
Ben Salah C., Ouali M. Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems. Electric Power Systems Research, 2011, vol. 81, no. 1, pp. 43-50. doi: https://doi.org/10.1016/j.epsr.2010.07.005.
Guldemir H. Sliding Mode Control of Dc-Dc Boost Converter. Journal of Applied Sciences, 2005, vol. 5, no. 3, pp. 588-592. doi: https://doi.org/10.3923/jas.2005.588.592.
Komurcugil H. Adaptive terminal sliding-mode control strategy for DC–DC buck converters. ISA Transactions, 2012, vol. 51, no. 6, pp. 673-681. doi: https://doi.org/10.1016/j.isatra.2012.07.005.
Bianconi E., Calvente J., Giral R., Mamarelis E., Petrone G., Ramos-Paja C.A., Spagnuolo G., Vitelli M. Perturb and Observe MPPT algorithm with a current controller based on the sliding mode. International Journal of Electrical Power & Energy Systems, 2013, vol. 44, no. 1, pp. 346-356. doi: https://doi.org/10.1016/j.ijepes.2012.07.046.
Chu C.-C., Chen C.-L. Robust maximum power point tracking method for photovoltaic cells: A sliding mode control approach. Solar Energy, 2009, vol. 83, no. 8, pp. 1370-1378. doi: https://doi.org/10.1016/j.solener.2009.03.005.
Meekhun D., Boitier V., Dilhac J., Blin G. An automated and economic system for measuring of the current-voltage characteristics of photovoltaic cells and modules. 2008 IEEE International Conference on Sustainable Energy Technologies, Singapore, 2008, pp. 144-148. doi: https://doi.org/10.1109/icset.2008.4746989.
Sholapur S., Mohan K.R., Narsimhegowda T.R. Boost Converter Topology for PV System with Perturb And Observe MPPT Algorithm. IOSR Journal of Electrical and Electronics Engineering, 2014, vol. 9, no. 4, pp. 50-56. doi: https://doi.org/10.9790/1676-09425056.
Youssef E.B., Stephane P., Bruno E., Corinne A. New P&O MPPT algorithm for FPGA implementation. IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society, Glendale, AZ, 2010, pp. 2868-2873. doi: https://doi.org/10.1109/iecon.2010.5675079.
Nebti K., Debbabi F. Amelioration of MPPT P&O Using Fuzzy-Logic Technique for PV Pumping. Renewable Energy for Smart and Sustainable Cities. ICAIRES 2018. Lecture Notes in Networks and Systems, 2019, vol. 62. Springer, Cham. doi: https://doi.org/10.1007/978-3-030-04789-4_43.
Ghazanfari J., Farsangi M.M. Maximum power point tracking using sliding mode control for photovoltaic array. Iranian Journal of Electrical and Electronic Engineering, 2013, vol. 9, no. 3, pp. 189-196. Available at: http://ijeee.iust.ac.ir/article-1-523-en.pdf. (accessed on 20 May 2020).
Chatrenour N., Razmi H., Doagou-Mojarrad H. Improved double integral sliding mode MPPT controller based parameter estimation for a stand-alone photovoltaic system. Energy Conversion and Management, 2017, vol. 139, pp. 97-109. doi: https://doi.org/10.1016/j.enconman.2017.02.055.
Vázquez N., Azaf Y., Cervantes I., Vázquez E., Hernández C. Maximum power point tracking based on sliding mode control. International Journal of Photoenergy, 2015, vol. 2015, pp. 1-8. doi: https://doi.org/10.1155/2015/380684.
Farhat M., Barambones O., Ramos J.A., Gonzalez de Durana J.M. Maximum power point tracking controller based on sliding mode approach. Conference Actas de las XXXV Jornadas de Automática, 3-5 September, 2014, Valencia. Available at: http://www.ja2014.upv.es/wp-content/uploads/papers/paper_7.pdf (accessed on 15 June 2020).
Wu X., Shen J., Li Y., Lee K.Y. Fuzzy modeling and stable model predictive tracking control of large-scale power plants. Journal of Process Control, 2014, vol. 24, no. 10, pp. 1609-1626. doi: https://doi.org/10.1016/j.jprocont.2014.08.007.
Lacrose V., Titli A. Fusion and hierarchy can help fuzzy logic controller designers. Proceedings of the Sixth IEEE International Conference on Fuzzy Systems, Barcelona, Spain, 1997. doi: https://doi.org/10.1109/fuzzy.1997.616335.
Chouder A, Guijoan F, Silvestre S. Simulation of fuzzy-based MPP tracker and performance comparison with perturb & observe method. Rеvuе des Energies Renouvelables. 2008, vol. 11, no. 4, pp. 577-586. Available at: https://www.asjp.cerist.dz/en/article/119627 (accessed on 25 July 2020).
Azzouzi M. Comparison between MPPT P&O and MPPT fuzzy controls in optimizing the photovoltaic generator. International Journal of Advanced Computer Science and Applications (IJACSA), 2012, vol. 3, no. 12, pp 57-62. doi: https://doi.org/10.14569/ijacsa.2012.031208.
Zhang C., Zhao D. MPPT with asymmetric fuzzy control for photovoltaic system. 2009 4th IEEE Conference on Industrial Electronics and Applications, Xi'an, 2009, pp. 2180-2183. doi: https://doi.org/10.1109/iciea.2009.5138584.
Noman A.M., Addoweesh K.E., Mashaly H.M. DSPACE Real-Time Implementation of MPPT-Based FLC Method. International Journal of Photoenergy, 2013, vol. 2013, pp. 1-11. doi: https://doi.org/10.1155/2013/549273.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 K. Nebti , R. Lebied
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.