Maximum Power Point Tracking in PV System with Home Applications
The use of photovoltaic energy in modern transmission systems is increasingly preferred due to its environmentally friendly features. Modular photovoltaics show a nonlinear correlation between the generated power and the environmental conditions. This study presents a Maximum Power Point Tracker (MPPT) based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) to optimize solar power systems. The designed controller optimizes the output power of a DC-DC converter linked to a 250W solar array. The complete analysis of the model is done using MATLAB/SIMULINK, considering the key characteristics of the technical data. The controller behavior is evaluated under diverse weather conditions. The paper suggests that the controller is effective in tracking peak power of the panel.
Ansari MF, Kharb RK, Luthra S, Shimmi SL, Chatterji S. Analysis of barriers to implement solar power installations in India using interpretive structural modeling technique. Renew Sustain Energy Rev 2013;27:163–74
Blakers A, Wright PD, Gazzoni DL, Hestnes AG, Kituyi E, Kretzschmar J, et al. Research and development on renewable energies. A global report on photovoltaic and wind energy, ISPRE; December 2009.
Rustemli S, Dincer F, Almali MN. Research on effects of environmental factors on photovoltaic panels and modeling with Matlab/Simulink. Przegląd elektrotechniczny (Electrical Review), ISSN 0033-2097, R. 88 NR 7a/2012.
Alamoudi, R., Taylan, O., Aktacir, M. A., & Herrera-Viedma, E., Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysisand Adjustment Based on RSM and ANFIS Approaches. Mathematics, 2021, 9(22).
doi:ARTN 2929 10.3390/math9222929.
Joe-Air J, Jen-Cheng W, Kun-Chang K, Yu-Li S, Jyh-Cherng S, Jui-Jen C. Analysis of the junction temperature and thermal characteristics of photovoltaic modules under various operation conditions. Energy 2012;44:292–301
Karafil, A., & Özbay, H., Design of Stand-Alone PV System on a Farm House in Bilecik City, Turkey. El-Cezeri Journal of Science and Engineering, 2018, 5(3), 909-916.
Borenstein S. The market value and cost of solar photovoltaic electricity production. Center for the Study of Energy Markets (CSEM) working paper 176; January 2008.
Lingareddy V, Ravichandra G, Maddukrui PK. Effective strategy for MPPT in PV/wind hybrid electric power system interconnected with electrical utility grid. Int J Adv Res Comput Sci Softw Eng 2013.
Z. Kesilmiş, “A manhattan metric based perturb and observe maximum power point tracking algorithm for photovoltaic systems,” Energy Sources, Part A Recover. Util. Environ. Eff., vol. 44, pp. 469–492, 2022, doi: 10.1080/15567036.2022.2046662.
Lokanadham M, Bhaskar KV. Incremental conductance based Maximum Power Point Tracking (MPPT) for photovoltaic system. Int J Eng Res Appl 2248-9622 2012;2(2):1420–4.
Moubayed N, El-Ali A, Outbib R. A comparison of two MPPT techniques for PV system. WSEAS Trans Environ Dev 2009;5(12).
Yetayew, T. T., Jyothsna, T. R., & Kusuma, G., 2016. Evaluation of Incremental conductance and Firefly algorithm for PV MPPT application under partial shade condition. In Power Systems (ICPS), 2016 IEEE 6th International Conference on IEEE, 1-6.
Esram T, Chapman PL. Comparison of photovoltaic array maximum power point tracking techniques. IEEE Trans Energy Convers 2007;22
Wu YE, Shen CL, Wu CY. Research and improvement of maximum power point tracking for photovoltaic systems. In: Proceedings of the 8th international conference on power electronics and drive systems. Taipei, Taiwan; November 2–5, 2009.
Mahmoud AMA, Mashaly HM, Kandil SA, Khashab HEL, Nashed MNF. Fuzzy logic implementation for photovoltaic maximum power tracking. In: Proceedings of the IEEE international workshop on robot and human interactive communication. Osaka. Japan; September 27–29, 2000.
Balamurugan T, Manoharan S. Fuzzy controller design using soft switching boost converter for MPPT in hybrid system. Int J Soft Comput Eng2231-2307 2012;2(5).
Patcharaprakiti N, Premrudeepreechacharn S, Sriuthaisiriwong Y. Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system. Elsevier Ltd.; 2005.
Esram T, Chapman PL. Comparison of photovoltaic array maximum power point tracking techniques. IEEE Trans Energy Convers 2007;22(2).
Liu C, Wu B, Cheung R. Advanced algorithm for MPPT control of photovoltaic systems. In: Proceedings of the Canadian solar buildings conference. Montreal; August 20–24, 2004
Sedaghati F, Nahavandi A, Badamchizadeh MA, Ghaemi S, Fallah MA. PV maximum power-point tracking by using artificial neural network. Math Prob Eng 2012:1–10 (Article ID 506709).
T. Takagi and M. Sugeno, "Derivation of Fuzzy Control Rules from Human Operator’s Control Action", IFAC Proceedings Volumes, vol. 16, pp.55–60 July 1983. https://doi.org/10.1016/S1474-6670(17)62005-6.
E. H. Mamdani and S. Assilian, "An experiment in linguistic synthesis with a fuzzy logic controller", International Journal of Man-Machine Studies, vol. 7, pp.1-13, January 1975.
https://doi.org/10.1016/S0020- 7373(75)80002-2.
