Master of Science (MS)
Electrical and Computer Engineering
Distributed generation networks including micro grids benefit from solar cells that are controlled by dc-dc converters. In this research a nonlinear discrete-time model for a buck converter tied to a solar system is derived with unknown internal dynamics. Then, adaptive neural network (NN) controller is employed to enhance stability of dc-dc converter connected to grid-tie inverter (GTI) in the presence of power system disturbances. The NN weights are tuned online by using a novel update law. By using Lyapunov techniques, all signals can be shown to be uniformly ultimately bounded (UUB). In addition, the interaction of the converter with the GTI is investigated to assure stability of the entire interconnected system while the GTI is controlled via a novel stabilizer similar to power system stabilizer (PSS). The proposed nonlinear discrete-time converter controller along with the GTI, equipped with PSS, is simulated in Matlab Simulink environment. The results have highlighted the effectiveness of the proposed modeling and controller design.
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Kazemlou, Shaghayegh, "Discrete time modeling and control of DC/DC switching converter for solar energy systems" (2013). LSU Master's Theses. 422.