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Zhang, L., Bai, Y.F. and Al-Amoudi, A. (2002) GA-RBF Neural Network Based Maximum Power Point Tracking for Grid-Connected Photovoltaic Systems. International Conference on Power Electronics, Machines and Drives, 4-7 June 2002, 18-23.

has been cited by the following article:

• TITLE: Overview of Maximum Power Point Tracking Control Methods for PV Systems

  AUTHORS: Saleh Elkelani Babaa, Matthew Armstrong, Volker Pickert

  KEYWORDS: Photovoltaic (PV) System, Boost Converter, Maximum Power Point Tracking (MPPT)

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.2 No.8, August 28, 2014

  ABSTRACT: Maximum power point tracking (MPPT) controllers play an important role in photovoltaic systems. They maximize the output power of a PV array for a given set of conditions. This paper presents an overview of the different MPPT techniques. Each technique is evaluated on its ability to detect multiple maxima, convergence speed, ease of implementation, efficiency over a wide output power range, and cost of implementation. The perturbation and observation (P & O), and incremental conductance (IC) algorithms are widely used techniques, with many variants and optimization techniques reported. For this reason, this paper evaluates the performance of these two common approaches from a dynamic and steady state perspective.