This work presents the supervision strategy in an Arduino card PV generator with storage connected to the low voltage grid. The studied system is composed of a photovoltaic generator, a boost converter, a buck-boost converter and a singlephase inverter. The power of the PV module depends on atmospheric conditions. Batteries are often confronted with overload problems and underload. The objective of this article is to manage the charging and discharging of the batteries, taking into account their protection against overload and under load and supervise the system. For this, supervision algorithms implemented in Arduino developed. Simulation results under Matlab show that the Arduino board has ensured the protection of the batteries and system supervision.
This paper presents the meta-heuristic and conventional optimizations techniques for the grid connected photovoltaic solar system. The perturb and observe (P&O) and particle swarm optimization (PSO) algorithms are proposed to track the maximum power point (MPP) of the photovoltaic solar system (PVSS). The regularization of the current supplied into the grid is ensured by the proportional integral (PI) corrector whose parameters are generated by the genetic algorithm (GA). The results of these two MPPT methods are compared and showed that the PSO is more efficient than the P&O. The use of GA algorithm to determine PI parameters allowed to obtain 0.89% of total distortion harmonic (THD).
This study shows a neural network based control strategy of the current injected into a single-phase grid via an inverter. The inverter is supplied by a Photovoltaic Generator (PVG). The optimal control of PVG is ensured by an MPPT algorithm of type P and O (Perturbation-Observation). The synchronization of the inverter with the electrical grid is ensured by a Phase-Locked Loop (PLL) device. The sizing and the modeling of the system components have been presented. A Neural Network Controller (NNC) and a Proportional Integral (PI) controller have been implemented and compared. Obtained results show that the NNC have faster response and lower THD without overshoots.
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