A Novel Adaptive Neural MPPT Algorithm for Photovoltaic System


  • S. A. Allahyari Mehriz Branch, Islamic Azad University, Mehriz, Iran
  • Nasser Taheri Electrical Engineering Department, Technical and Vocational University, Sabzevar, Iran
  • M. Zadehbagheri Yasouj Branch, Islamic Azad University, Kohgiloyeh & Bovirahmad Province, Yasouj, Iran
  • Z. Rahimkhani Sarvestan Branch, Islamic Azad University, Sarvestan, Iran




Photovoltaic systems; adaptive neural networks; MPPT algorithm


This paper presents a novel adaptive neural network (ANN) for maximum power point tracking (MPPT) in photovoltaic (PV) systems under variable working conditions. The ANN-based MPPT model includes two separate NNs for PV system identification and control. NNs are trained by using of a novel back propagation algorithm in pre/post control phases. Because of online optimal performance of NNs, the proposed method, not only overcome the common drawbacks of the conventional MPPT methods, but also gives a simple and a robust MPPT scheme. Simulation results, which carried on MATLAB, show that proposed controller is the most effective in comparison with conventional MPPT approaches.




How to Cite

S. A. Allahyari, N. Taheri, M. Zadehbagheri, and Z. Rahimkhani, “A Novel Adaptive Neural MPPT Algorithm for Photovoltaic System”, Int. J. Automot. Mech. Eng., vol. 15, no. 3, pp. 5421–5434, Oct. 2018.