A Hybrid of Fuzzy Logic and Sliding Mode Techniques for Photovoltaic Maximum Power Point Tracking Systems Under Partial Shading
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University of Nairobi Research Archive
Solar energy harvesting using photovoltaic (PV) modules have been one of the most commonsources of renewable energy for several decades. These modules have been used as a sourceof electricity for households, industries, in stand-alone, and grid-connected solar plants. Themodules consist of semi-conductor solar cells combined in series and parallel. In order to makea solar system, the modules are usually linked in series. The performance of a solar system isaffected by environmental factors like varying radiance and temperatures, shadowing caused byhigh-rise buildings, birds, fog, trees and dust. Such varying environmental conditions affect asolar cell's efficiency. Nevertheless, given all the effort made to mitigate the impact of all theseenvironmental 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 ciencyof 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 trackingthe maximum power point that have been used in this study. The application of these twoapproaches substantially increases system e ciency for all environmental conditions includingpartial shading instances. The sliding mode technique is a very fast, stable and robust algorithmthat work e ectively under very stable weather condition while the fuzzy logic has beenexploited under partial shading conditions. Both methods rely heavily on a good understandingof the characteristics of PV modules, which are studied using I-V, P-V or P-I curves. In thiswork, three new algorithms have been used to simulate and model the characteristics of a PVmodule.The algorithms are based on a single diode equivalent circuit, which has been chosen dueto the simplicity of simulation and modeling and provides a fast convergence time. The algorithmsare classi ed according to the method of obtaining the best values of the unknownve parameters of the diode model. Ideality factor (A), saturation current (Io), photocurrentiv(Iph), series (Rs) and parallel (Rp) resistances are the ve unknown parameters to be determinedfor characterization of a PV module using a diode model. These parameters have beenextracted using the I-V curve's three critical points at short circuit point (SCP), open circuitpoint (OCP) and maximum power point (MPP). The rst algorithm has been based on thechoice of ideality factor below the optimal ideality factor (Ao), such that 0 A Ao, whereasthe other parameters depends heavily on the choice of A. The second algorithm has been basedon the choice of ideality factor in the neighborhood of Ao and the third algorithm has beenbased on A Ao. The three methods have been utilized to characterize the solar module usingI-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 havecarefully selected from Kyocera- KC130CGT. Additional experimental work has been carriedout at Solinc Kenya Ltd using Solinc 60Wp and 250Wp PV modules, similar to those mountedon the rooftop of the building in Chiromo at School of Physical Sciences.