A Hybrid of Fuzzy Logic and Sliding Mode Techniques for Photovoltaic Maximum Power Point Tracking Systems Under Partial Shading
View/ Open
Date
2020Author
Gathoni, Robinson N
Type
ThesisLanguage
enMetadata
Show full item recordAbstract
Solar energy harvesting using photovoltaic (PV) modules have been one of the most common
sources of renewable energy for several decades. These modules have been used as a source
of electricity for households, industries, in stand-alone, and grid-connected solar plants. The
modules consist of semi-conductor solar cells combined in series and parallel. In order to make
a solar system, the modules are usually linked in series. The performance of a solar system is
affected by environmental factors like varying radiance and temperatures, shadowing caused by
high-rise buildings, birds, fog, trees and dust. Such varying environmental conditions affect a
solar cell's efficiency. Nevertheless, given all the effort made to mitigate the impact of all these
environmental threats, some of the natural occurrences such as varying radiance, clouds, dust,
wind-speed and change in temperature, can not be done away with. To improve the e ciency
of the entire solar system, power extraction must be optimized under all weather conditions.
Fuzzy logic and sliding mode techniques are e cient, fast and reliable methods of tracking
the maximum power point that have been used in this study. The application of these two
approaches substantially increases system e ciency for all environmental conditions including
partial shading instances. The sliding mode technique is a very fast, stable and robust algorithm
that work e ectively under very stable weather condition while the fuzzy logic has been
exploited under partial shading conditions. Both methods rely heavily on a good understanding
of the characteristics of PV modules, which are studied using I-V, P-V or P-I curves. In this
work, three new algorithms have been used to simulate and model the characteristics of a PV
module.
The algorithms are based on a single diode equivalent circuit, which has been chosen due
to the simplicity of simulation and modeling and provides a fast convergence time. The algorithms
are classi ed according to the method of obtaining the best values of the unknown
ve parameters of the diode model. Ideality factor (A), saturation current (Io), photocurrent
iv
(Iph), series (Rs) and parallel (Rp) resistances are the ve unknown parameters to be determined
for characterization of a PV module using a diode model. These parameters have been
extracted using the I-V curve's three critical points at short circuit point (SCP), open circuit
point (OCP) and maximum power point (MPP). The rst algorithm has been based on the
choice of ideality factor below the optimal ideality factor (Ao), such that 0 A Ao, whereas
the other parameters depends heavily on the choice of A. The second algorithm has been based
on the choice of ideality factor in the neighborhood of Ao and the third algorithm has been
based on A Ao. The three methods have been utilized to characterize the solar module using
I-V and P-V curves and have output power errors of less than 0.5%.
For proof of concept of the three algorithms, PV module with IEC61215 speci cations have
carefully selected from Kyocera- KC130CGT. Additional experimental work has been carried
out at Solinc Kenya Ltd using Solinc 60Wp and 250Wp PV modules, similar to those mounted
on the rooftop of the building in Chiromo at School of Physical Sciences.
Publisher
University of Nairobi
Rights
Attribution-NonCommercial-NoDerivs 3.0 United StatesUsage Rights
http://creativecommons.org/licenses/by-nc-nd/3.0/us/Collections
The following license files are associated with this item: