In this study, a model reference adaptive state-dependent Riccati equation (MRASDRE) is proposed as a maximum power point tracking (MPPT) controller to extract the maximum power from a photovoltaic (PV) array mounted on an orbiting satellite. In the structure of the proposed MPPT, a fuzzy logic controller (FLC) is used to estimate the reference voltage of the PV array at the maximum power point (MPP), and an adaptive mechanism is used to compensate for the difference between the PV system and the reference model. The model reference generates the duty cycle for damping the oscillations of the DC-DC converter and tracking the MPP. A Lyapunov stability theory is used to obtain an adaption law to tune the gains of the adaptive mechanism. Hence, the stability of the closed system can be guaranteed, and the maximum power point (MPP) can be captured. To evaluate the performance of the proposed MPPT used in an orbiting satellite, the outer space environment is simulated. Also, an electrical power supply (EPS) is proposed to manage the generation and consumption of satellites. The efficiency of the proposed MPPT is verified in the simulation tests.
This paper considers the problem of tracking the global maximum power point (GMPP) in partially shaded conditions (PSCs) as a multiobjective optimization problem and solves it using a novel multiobjective optimization algorithm on the basis of Bayesian optimization formulation. Bayesian optimization is a metamodel-based global optimization method that is able to balance exploration and exploitation. The Pareto solutions are obtained by using a multiobjective Bayesian optimization algorithm. Also, a new acquisition function is proposed to improve the diversity and convergence of the Pareto solutions. Two objective functions are introduced to remove the large tracking errors and oscillations of the operating point around the GMPP. The suggested method is implemented online for GMPP tracking so that the suggested method monitors any change in environmental conditions and generates the optimal duty cycle for the DC-DC converter for the GMPP tracking (GMPPT) by the PV array. Several multipeak PSC scenarios are implemented and simulated to show efficiency of the suggested approach. The MATLAB/SIMULINK is employed to implement a photovoltaic (PV) system comprising a PV array, a boost converter, and the proposed multiobjective Bayesian optimization algorithm (MOBOA). The simulation results show a very satisfactory performance of the MOBOA in terms of transient state and steady-state oscillations and tracking speed.
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