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.