Saxena, A.R. and Gupta, S.M. (2014) Performance Analysis of P & O and Incremental Conductance MPPT Algorithms under Rapidly Changing Weather Conditions. Journal of Electrical Systems, 10, 292-304.

has been cited by the following article:

• TITLE: Simulations of the Performance of Maximum Power Point Tracking Algorithms Based on Experimental Data According to the Topologies of DC-DC Converters

  AUTHORS: Abraham Dandoussou, Pierre Kenfack, Stève Ngoffe Perabi, Martin Kamta

  KEYWORDS: MPPT Algorithms, DC-DC Converters, Photovoltaic Parameters, Normal Operating Conditions

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.9 No.5, May 22, 2021

  ABSTRACT: Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous performance test under normal weather conditions. This paper proposes an experimental evaluation of MPPT algorithms according to DC-DC converters topologies, under normal operation conditions. Four widely used MPPT algorithms i.e. Perturb and Observe (P & O), Hill Climbing (HC), Fixed step Increment of Conductance (INCF) and Variable step Increment of Conductance (INCV) are implemented using two topologies of DC-DC converters i.e. buck and boost converters. As input variables to the PV systems, recorded irradiance and temperature, and extracted photovoltaic parameters (ideality factor, series resistance and reverse saturation current) were used. The obtained results show that buck converter has a lot of power losses when controlled by each of the four MPPT algorithms. Meanwhile, boost converter presents a stable output power during the whole day. Once more, the results show that INCV algorithm has the best performance.