Abstract
Photovoltaic (PV) systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP). Diverse offline and online techniques have been introduced for tracking the MPP. Here, to track the MPP, an augmented-state feedback linearized (AFL) non-linear controller combined with an artificial neural network (ANN) is proposed. This approach linearizes the non-linear characteristics in PV systems and DC/DC converters, for tracking and optimizing the PV system operation. It also reduces the dependency of the designed controller on linearized models, to provide global stability. A complete model of the PV system is simulated. The existing maximum power-point tracking (MPPT) and DC/DC boost-converter controller techniques are compared with the proposed ANN method. Two case studies, which simulate realistic circumstances, are presented to demonstrate the effectiveness and superiority of the proposed method. The AFL with ANN controller can provide good dynamic operation, faster convergence speed, and fewer operating-point oscillations around the MPP. It also tracks the global maxima under different conditions, especially irradiance-mutating situations, more effectively than the conventional methods. Detailed mathematical models and a control approach for a three-phase grid-connected intelligent hybrid system are proposed using MATLAB/Simulink.
Highlights
Global energy consumption has increased noticeably because of the population explosion.The sustainable use of renewable energy solves one of the major concerns of the world community, since fossil energy sources will not last forever [1]
System uses a DC/DC converter to isolate the operating point of the generator from the load. Such a power converter is regulated by an algorithm that searches for the maximum power point (MPP, i.e., the optimal operation condition); this algorithm is known as the maximum
This paper proposes an Augmented-State Feedback Linearization (AFL) controller based on a DC/DC converter, which can solve the
Summary
Global energy consumption has increased noticeably because of the population explosion.The sustainable use of renewable energy solves one of the major concerns of the world community, since fossil energy sources will not last forever [1]. Global energy consumption has increased noticeably because of the population explosion. The PV generator, known as PV array, produces DC power that depends on the environmental conditions and the operating point imposed by the load. To provide a large amount of power, the PV system uses a DC/DC converter to isolate the operating point of the generator (voltage and current) from the load. Such a power converter is regulated by an algorithm that searches for the maximum power point (MPP, i.e., the optimal operation condition); this algorithm is known as the maximum
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