Advertisement

An Improved Algorithm for Maximum Power Point Tracking of Photovoltaic Cells Based on Newton Interpolation Method

  • Yuanyuan Li
  • Sumin Han
  • Fuzhong Wang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 528)

Abstract

Photovoltaic (PV) arrays are power generation equipment in PV systems. Maximum power point Tracking (MPPT) scheme in the PV array affects the power generation efficiency of the PV system. In this paper, based on the deficiencies of existing MPPT methods, an algorithm by combining the increment conductance method with variable step size and Newton interpolation method is proposed, which can automatically adjust the step size according to changes in the external environment to avoid power loss and improve the photovoltaic power generation efficiency. The results show the improved MPPT algorithm can efficiently control the vibration amplitude of the power waveform output compared with the traditional conductance increment method. The problem studied in this paper is somewhat interesting. I have the following comments. Meanwhile, it presents a faster tracking speed and a good adaptability for the environment.

Keywords

Maximum power point tracking Newton interpolation Variable step length Conductance increment method Photovoltaic array 

References

  1. 1.
    B. Sun, J. Mei, J. Zheng, An improved algorithm for maximum power point tracking under local shadow conditions. Electr. Power Autom. Equip. 34(01), 115–119+127 (2014)Google Scholar
  2. 2.
    L. Zhou, J. Wu, Q. Liu, et al., Survey of PV array maximum power point tracking control method. High Volt. Eng. (06), 1145–1154 (2008)Google Scholar
  3. 3.
    G. Wu, X. Li, Application of Newton interpolation method in maximum power tracking of photovoltaic power generation. Power Technol. 39(7), 1432–1434 (2015)Google Scholar
  4. 4.
    R.I. Putri, S. Wibowo, M. Rifa’i, Maximum power point tracking for photovoltaic using incremental conductance method. Energy Procedia 68, 22–30 (2015)Google Scholar
  5. 5.
    M.H. Moradi, A.R. Reisi, A hybrid maximum power point tracking method for photovoltaic systems. Sol. Energy 85(11), 2965–2976 (2011)CrossRefGoogle Scholar
  6. 6.
    Y. Jia, Robust control with decoupling performance for steering and traction of 4WS vehicles under velocity-varying motion. IEEE Trans. Control Syst. Technol. 8(3), 554–569 (2000)Google Scholar
  7. 7.
    J. Hu, J. Zhang, Research on MPPT control algorithm for photovoltaic power generation system based on numerical method. Power Sci. Eng. 25(07), 1–6 (2009)Google Scholar
  8. 8.
    Y. Liu, K. Ying, H. Xin, et al., Control strategy of photovoltaic power generation system based on quadratic interpolation method. Autom. Electr. Power Syst. 36(21), 29–35 (2012)Google Scholar
  9. 9.
    Y. Jia, Alternative proofs for improved LMI representations for the analysis and the design of continuous-time systems with polytopic type uncertainty: a predictive approach. IEEE Trans. Autom. Control 48(8), 1413–1416 (2003)Google Scholar
  10. 10.
    X. Wen, Application Design of MATLAB Neural Network (Science Press, Beijing, 2001), pp. 35–72Google Scholar
  11. 11.
    J. Jiang, Design and transient simulation of grid-connected photovoltaic system controlled by improved MPPT (Yanshan University, 2013)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Electrical Engineering and AutomationHenan Polytechnic UniversityJiaozuoChina

Personalised recommendations