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Maximum power point tracking algorithm for photovoltaic home power supply.

dc.contributor.advisorSaha, Akshay Kumar.
dc.contributor.authorNkashama, Cedrick Lupangu.
dc.date.accessioned2013-01-17T10:26:32Z
dc.date.available2013-01-17T10:26:32Z
dc.date.created2011
dc.date.issued2011
dc.descriptionThesis (M.Sc.Eng)-University of KwaZulu-Natal, Durban, 2011.en
dc.description.abstractSolar photovoltaic (PV) systems are distributed energy sources that are an environmentally friendly and renewable source of energy. However, solar PV power fluctuates due to variations in radiation and temperature levels. Furthermore, when the solar panel is directly connected to the load, the power that is delivered is not optimal. A maximum peak power point tracker is therefore necessary for maximum efficiency. A complete PV system equipped maximum power point tracking (MPPT) system includes a solar panel, MPPT algorithm, and a DC-DC converter topology. Each subsystem is modeled and simulated in a Matlab/Simulink environment; then the whole PV system is combined with the battery load to assess the overall performance when subjected to varying weather conditions. A PV panel model of moderate complexity based on the Shockley diode equation is used to predict the electrical characteristics of the cell with regard to changes in the atmospheric parameter of irradiance and temperature. In this dissertation, five MPPT algorithms are written in Matlab m-files and investigated via simulations. The standard Perturb and Observe (PO) algorithm along with its two improved versions and the conventional Incremental Conductance (IC) algorithm, also with its two-stage improved version, are assessed under different atmospheric operating conditions. An efficient two-mode MPPT algorithm combining the incremental conductance and the modified constant voltage methods is selected from the five ones as the best model, because it provides the highest tracking efficiencies in both sunny and cloudy weather conditions when compared to other MPPT algorithms. A DC-DC converter topology and interface study between the panel and the battery load is performed. This includes the steady state and dynamic analysis of buck and boost converters and allows the researcher to choose the appropriate chopper for the current PV system. Frequency responses using the state space averaged model are obtained for both converters. They are displayed with the help of Bode and root locus methods based on their respective transfer functions. Following the simulated results displayed in Matlab environment for both choppers, an appropriate converter is selected and implemented in the present PV system. The chosen chopper is then modeled using the Simulink Power Systems toolbox and validates the design specifications. The simulated results of the complete PV system show that the performances of the PV panel using the improved two-stage MPPT algorithm provides better steady state and fast transient characteristics when compared with the conventional incremental conductance method. It yields not only a reduction in convergence time to track the maximum power point MPP, but also a significant reduction in power fluctuations around the MPP when subjected to slow and rapid solar irradiance changes.en
dc.identifier.urihttp://hdl.handle.net/10413/8321
dc.language.isoen_ZAen
dc.subjectPhotovoltaic power systems.en
dc.subjectElectric current converters.en
dc.subjectAlgorithm.en
dc.subjectElectric power transmission--Direct current.en
dc.subjectDistributed generation of electric power.en
dc.subjectTheses--Electrical engineering.en
dc.titleMaximum power point tracking algorithm for photovoltaic home power supply.en
dc.typeThesisen

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