Maximizing Solar Harvest: Comparing P&O and Incremental Conductance MPPT Methods
DOI:
https://doi.org/10.56294/piii2024320Keywords:
Photovoltaic system, Perturb & Observe, Incremental Conductance, Maximum Power Point TrackingAbstract
This paper presents a comprehensive comparative study between two prominent Maximum Power Point Tracking (MPPT) algorithms: the Perturb and Observe (P&O) method and the Incremental Conductance method (IC). The study delves into their operational principles, efficiency, robustness, implementation complexity, response time, and sensitivity to parameter changes. Through theoretical analysis and numerical simulations, the strengths and limitations of each algorithm are thoroughly assessed, offering valuable insights for optimizing photovoltaic (PV) systems. These simulations utilize established mathematical models of PV systems and MPPT algorithms. The findings reveal nuanced differences between the P&O and Incremental Conductance methods. Incremental Conductance demonstrates superior efficiency, particularly in environments with dynamic irradiance levels and partial shading conditions, owing to its ability to dynamically adjust the operating point. However, it exhibits increased implementation complexity compared to the simpler and more robust P&O method. In conclusion, this comparative study offers valuable insights into MPPT algorithm optimization for PV systems. While Incremental Conductance excels in efficiency and adaptability, P&O remains a viable option for applications with limited computational resources or stable environmental conditions due to its simplicity and robustness.
References
1. Saroya Y, Anand K, Singh DK. A Comparative Study on MPPT Techniques for PV System. Intelligent Systems and Smart Infrastructure. 2023 Feb 16;225–35. http://dx.doi.org/10.1201/9781003357346-25
2. Sarang SA, Raza MA, Panhwar M, Khan M, Abbas G, Touti E, et al. Maximizing solar power generation through conventional and digital MPPT techniques: a comparative analysis. Scientific Reports. 2024 Apr 18;14(1).http://dx.doi.org/10.1038/s41598-024-59776-z
3. Khodair D, Shaker A, El Munim HEA, Saeed A, Abouelatta M. A Comparative Study Between Modified MPPT Algorithms Using Different Types of Solar Cells. 2020 2nd International Conference on Smart Power & Internet Energy Systems (SPIES). 2020 Sep 15; http://dx.doi.org/10.1109/spies48661.2020.9243057
4. BENCHIKH, S., JAROU, T., BOUTAHIR, M.K., NASRI, E., LAMRANI, R.: Improving photovoltaic system performance with artificial neural network control. Data and Metadata 2 (2023) https://doi.org/10.56294/dm2023144
5. Analyzing the Effects of Different MPPT Algorithms on Lithium-Ion Battery Degradation.
6. American Institute of Aeronautics and Astronautics (AIAA) (2023); http://dx.doi.org/10.2514/6.2023-1592.vid
7. Sabri K, El Maguiri O, Farchi A. Comparative Study of Different MPPT Algorithms for
8. Photovoltaic Systems under Partial Shading Conditions. 2021 9th International Renewable and
9. Sustainable Energy Conference (IRSEC). 2021; http://dx.doi.org/10.1109/irsec53969.2021.9741164
10. Barkat N, Iqbal Bhatti A. A Comparative Study of Different Modified Incremental Conductance MPPT Algorithms Under very Fast-Changing Atmospheric Conditions for Solar Charging Station. 2021 16th International Conference on Emerging Technologies (ICET); http://dx.doi.org/10.1109/icet54505.2021.9689795
11. Experimental Evaluation of MPPT algorithms: A Comparative Study. International Journal of Renewable Energy Research. 2021; http://dx.doi.org/10.20508/ijrer.v11i1.11797.g8164
12. Benchikh S, Jarou T, Nasri E, Roa L. Design of an Adaptive Neuro-Fuzzy Inference System for Photovoltaic System. Lecture Notes in Networks and Systems. 2023;352–8. http://dx.doi.org/10.1007/978-3-031-26254-8_50
13. Maurya AK, Kumar Rai A, Ahuja H. Comparative Analysis of Different MPPT Algorithms for Roof-Top Solar PV System. 2022 International Conference on Automation, Computing and
14. Renewable Systems (ICACRS). 2022 Dec 13; http://dx.doi.org/10.1109/icacrs55517.2022.10028987
15. A Comparative Study of Distinct Advanced MPPT Algorithms for a PV Boost Converter.
16. International Journal of Renewable Energy Research. 2021 Sep 1; http://dx.doi.org/10.20508/ijrer.v11i3.12079.g8282
17. Mokhlis M, Ferfra M, Vall HA, idrissi RE, Ahmed CC, Taouni A. Comparative Study Between the Different MPPT Techniques. 2020 5th International Conference on Renewable
18. Energies for Developing Countries (REDEC). 2020 Jun; http://dx.doi.org/10.1109/redec49234.2020.9163591
19. Boubii C, El Kafazi I, Bannari R, El Bhiri B. A Comparative Study Between MPC Algorithm and P&O and IncCond the Optimization Algorithms of MPPT Algorithms.
20. Lecture Notes in Networks and Systems. 2023;704–13. http://dx.doi.org/10.1007/978-3-03129857-8_70
21. A MATLAB Based Comparative Study Between Single and Hybrid MPPT Techniques for Photovoltaic Systems. International Journal of Renewable Energy Research. 2019; http://dx.doi.org/10.20508/ijrer.v9i4.9927.g7807
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Benchikh Salma, Jarou Tarik, Lamrani Roa (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
