A novel theta MPPT approach based on adjustable step size for photovoltaic system applications under various atmospheric conditions
Springer Science and Business Media LLC - Trang 1-26 - 2022
Tóm tắt
This study suggests and discusses a new maximum power point tracking (MPPT) approach based on an adjustable step size for photovoltaic system applications to extract the real MPP under various atmospheric conditions. The suggested adjustable step size Theta approach (ASSTA) is essentially based on the Theta angle (θ), which is the arctangent of the change in photovoltaic power derived by the variation in the photovoltaic voltage (arctan(dPpv/dVpv)) and its derivation in relation to the change in the photovoltaic voltage (dθ/dVpv) with the use of a new adaptable step size (dPpv + dVpv × dIpv). MATLAB/Simulink® software is selected for the implementation of the overall photovoltaic system, and the simulation results in different scenarios indicate that the novel ASSTA guarantees a fast convergence speed to the real MPP under a rapid change in operating conditions (insolation and temperature) with a time fewer than 0.017 s. Furthermore, the ASSTA shows better accuracy in tracking the MPP in the case of sudden insolation and temperature change and tracks the real MPP with neglected fluctuation in steady-state operation. Its average tracking efficiency in all simulation scenarios can be between 99.10 and 99.81%. Additionally, in light of the comparative simulation results of the new ASSTA with other methods such as INC, P&O, variable step size INC (VSSINC), and PSO MPPT techniques under various climatic scenarios, it can be concluded that the novel ASSTA outperforms the other MPPT approaches and significantly boosts the tracking performance and reduces power loss.
Tài liệu tham khảo
Al-Majidi, S.D., Abbod, M.F., Al-Raweshidy, H.S.: A particle swarm optimisation-trained feedforward neural network for predicting the maximum power point of a photovoltaic array. Eng Appl Artif Intell 92, 103688 (2020). https://doi.org/10.1016/J.ENGAPPAI.2020.103688
Boulakhbar, M., Lebrouhi, B., Kousksou, T., Smouh, S., Jamil, A., Maaroufi, M., et al.: Towards a large-scale integration of renewable energies in Morocco. J Energy Storage 32, 101806 (2020). https://doi.org/10.1016/J.EST.2020.101806
Das, B.K., Alotaibi, M.A., Das, P., Islam, M.S., Das, S.K., Hossain, M.A.: Feasibility and techno-economic analysis of stand-alone and grid-connected PV/Wind/Diesel/Batt hybrid energy system: a case study. Energy Strateg Rev 37, 100673 (2021). https://doi.org/10.1016/J.ESR.2021.100673
El-Houari H, Allouhi A, Rehman S, Buker MS, Kousksou T, Jamil A, et al. Design, Simulation, and Economic Optimization of an Off-Grid Photovoltaic System for Rural Electrification 2019. https://doi.org/10.3390/en12244735.
Manoharan P, Subramaniam U, Babu TS, Padmanaban S, Holm-Nielsen JB, Mitolo M, et al. Improved Perturb and Observation Maximum Power Point Tracking Technique for Solar Photovoltaic Power Generation Systems. IEEE Syst J 2021;15. https://doi.org/10.1109/JSYST.2020.3003255.
Sarvi, M., Azadian, A.: A comprehensive review and classified comparison of MPPT algorithms in PV systems. Energy Syst (2021). https://doi.org/10.1007/s12667-021-00427-x
Chellakhi A, El Beid S, Abouelmahjoub Y. Implementation of a novel MPPT tactic for PV system applications on MATLAB/simulink and proteus-based arduino board environments. Int J Photoenergy 2021;2021. https://doi.org/10.1155/2021/6657627.
Yang B, Zhu T, Wang J, Shu H, Yu T, Zhang X, et al. Comprehensive overview of maximum power point tracking algorithms of PV systems under partial shading condition. J Clean Prod 2020;268. https://doi.org/10.1016/j.jclepro.2020.121983.
Li X, Wen H, Hu Y, Du Y, Yang Y. A Comparative study on photovoltaic MPPT algorithms under EN50530 dynamic test procedure. IEEE Trans Power Electron 2021;36. https://doi.org/10.1109/TPEL.2020.3024211.
Nadeem A, Sher HA, Murtaza AF. Online fractional open-circuit voltage maximum output power algorithm for photovoltaic modules. IET Renew Power Gener 2020;14. https://doi.org/10.1049/iet-rpg.2019.0171.
Claude Bertin Nzoundja Fapi, Wira P, Kamta M, Tchakounté H, Colicchio B. Simulation and dSPACE hardware implementation of an improved fractional short-circuit current MPPT algorithm for photovoltaic system. Appl Sol Energy (English Transl Geliotekhnika) 2021;57. https://doi.org/10.3103/S0003701X21020080.
Chellakhi A, El Beid S, Abouelmahjoub Y. An Improved maximum power point approach for temperature variation in PV system applications. Int J Photoenergy 2021;2021. https://doi.org/10.1155/2021/9973204.
Abdelkhalek C, Said ELB, Younes A. Ripples amplitude minimizing of the output boost converter using an innovative MPPT controller for PV systems applications. 2020 IEEE 2nd Int. Conf. Electron. Control. Optim. Comput. Sci., 2020, p. 1–6
Abdelkhalek C, Said EB, Younes A. A novel MPPT tactic for PV systems with fast-converging speed and zero oscillation. 2020 5th Int. Conf. Renew. Energies Dev. Countries, REDEC 2020, 2020. https://doi.org/10.1109/REDEC49234.2020.9163606.
Nzoundja Fapi CB, Wira P, Kamta M, Badji A, Tchakounte H. Real-time experimental assessment of hill climbing MPPT algorithm enhanced by estimating a duty cycle for PV system. Int J Renew Energy Res 2019;9.
Mohammad ANM, Radzi MAM, Azis N, Shafie S, Zainuri MAAM. An enhanced adaptive perturb and observe technique for effcient maximum power point tracking under partial shading conditions. Appl Sci 2020;10. https://doi.org/10.3390/app10113912.
Gopahanal Manjunath M, Vyjayanthi C, Modi CN. Adaptive step size based drift-free P&O algorithm with power optimiser and load protection for maximum power extraction from PV panels in stand-alone applications. IET Renew Power Gener 2021;15. https://doi.org/10.1049/rpg2.12105.
Ali MN, Mahmoud K, Lehtonen M, Darwish MMF. An efficient fuzzy-logic based variable-step incremental conductance MPPT method for grid-connected PV systems. IEEE Access 2021;9. https://doi.org/10.1109/ACCESS.2021.3058052.
Mohammadinodoushan M, Abbassi R, Jerbi H, Waly Ahmed F, Abdalqadir kh ahmed H, Rezvani A. A new MPPT design using variable step size perturb and observe method for PV system under partially shaded conditions by modified shuffled frog leaping algorithm- SMC controller. Sustain Energy Technol Assessments 2021;45. https://doi.org/10.1016/j.seta.2021.101056.
Wang SC, Pai HY, Chen GJ, Liu YH. A Fast and Efficient Maximum Power Tracking Combining Simplified State Estimation with Adaptive Perturb and Observe. IEEE Access 2020;8. https://doi.org/10.1109/ACCESS.2020.3019197.
Srinivasarao P, Peddakapu K, Mohamed MR, Deepika KK, Sudhakar K. Simulation and experimental design of adaptive-based maximum power point tracking methods for photovoltaic systems. Comput Electr Eng 2021;89. https://doi.org/10.1016/j.compeleceng.2020.106910.
Ait Ayad I, Elwarraki E, Baghdadi M. Intelligent perturb and observe based MPPT approach using multilevel DC-DC converter to improve PV production system. J Electr Comput Eng 2021;2021. https://doi.org/10.1155/2021/6673022.
Ali MN, Mahmoud K, Lehtonen M, Darwish MMF. Promising mppt methods combining metaheuristic, fuzzy-logic and ann techniques for grid-connected photovoltaic. Sensors (Switzerland) 2021;21. https://doi.org/10.3390/s21041244.
Farajdadian S, Hosseini SMH. Design of an optimal fuzzy controller to obtain maximum power in solar power generation system. Sol Energy 2019;182. https://doi.org/10.1016/j.solener.2019.02.051.
Inthamoussou FA, Valenciaga F. A fast and robust closed-loop photovoltaic MPPT approach based on sliding mode techniques. Sustain Energy Technol Assessments 2021;47. https://doi.org/10.1016/j.seta.2021.101499.
Chao KH, Rizal MN. A hybrid mppt controller based on the genetic algorithm and ant colony optimization for photovoltaic systems under partially shaded conditions. Energies 2021;14. https://doi.org/10.3390/en14102902.
Basha CH, Rani C. Different conventional and soft computing MPPT techniques for solar PV systems with high step-up boost converters: A comprehensive analysis. Energies 2020;13. https://doi.org/10.3390/en13020371.
Rodrigues EMG, Godina R, Marzband M, Pouresmaeil E. Simulation and comparison of mathematical models of PV cells with growing levels of complexity. Energies 2018;11. https://doi.org/10.3390/en11112902.
Yilmaz, U., Kircay, A., Borekci, S.: PV system fuzzy logic MPPT method and PI control as a charge controller. Renew Sustain Energy Rev 81, 994–1001 (2018). https://doi.org/10.1016/J.RSER.2017.08.048
Vinod, Kumar R, Singh SK. Solar photovoltaic modeling and simulation: As a renewable energy solution. Energy Reports 2018;4. https://doi.org/10.1016/j.egyr.2018.09.008.
Bhukya MN, Kota VR. A quick and effective MPPT scheme for solar power generation during dynamic weather and partial shaded conditions. Eng Sci Technol an Int J 2019;22. https://doi.org/10.1016/j.jestch.2019.01.015.
MATLAB, 2018. version 9.4.0 (R2018a) n.d. The MathWorks Inc., Natick, Massachusetts, United States.
Alajmi BN, Ahmed KH, Finney SJ, Williams BW. A maximum power point tracking technique for partially shaded photovoltaic systems in microgrids. IEEE Trans Ind Electron 2013;60. https://doi.org/10.1109/TIE.2011.2168796.
Ji YH, Jung DY, Kim JG, Kim JH, Lee TW, Won CY. A real maximum power point tracking method for mismatching compensation in PV array under partially shaded conditions. IEEE Trans Power Electron 2011;26. https://doi.org/10.1109/TPEL.2010.2089537.