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 work is devoted to the study of a photovoltaic system connected to the distribution grid. The objective is to propose a new corrector for the control of a three-phase inverter connected to the distribution grid in order to obtain an optimal injection of photovoltaic energy. The system consists of a photovoltaic generator, a DC/DC boost converter and a three-phase inverter connected to the grid via a transformer. In first, a system modeling has established the mathematical models of the different components of the conversion chain. A local method of research maximum power point of the incremental conductance type (InC) is then developed. Furthermore, a control in the synchronous reference frame d-q by a modified PID controller is offered to regulate the currents injected by the three-phase inverter compared to conventional PI and PID controllers. Simulation results from the system under the Matlab/Simulink environment prove the efficiency of the MPPT control and show that the currents injected with the modified PID controller have a the best sinusoidal form with a harmonic distortion rate (TDH) of 2.39%.

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The best quality of PV energy into the grid is now problematic that is why this paper focuses on the design and implementation of a robust Proportional Integral Derivative based on Artificial Neural Network (ANN-PID). This technique used to ensure the regulation of the Boost Converter (BC) output voltage and the Three Phase Inverter (3 PI) output currents of a photovoltaic solar system (PVS) connected to the grid. The mathematical model of the DC bus and the 3-PI is presented. Applications under Matlab/Simulink justify the efficiency of the neural regulator. In comparison with the conventional one, the proposed method presents the best follow-up of the DC link voltage reference and a maximum overshoot of 3.16 %. In addition, despite the long time put in transient mode, the proposed method keeps better robustness and ensures an injection of current of a total harmonic distortion (THD) of 0.96 % against 2.18 % of the classical PID regulator.

This paper is devoted to the study of a photovoltaic system connected to the grid. The objective is to provide a novel approach based on artificial neural networks for Controlling the three-phase invelter in order to ensure a flexible injection to unity power factor and low total harmonic dist01tion. A modeling system established mathematical models of the invener and the DC link. A control in the synchronous reference direct and quadratic frame by a neural proportional integral derivative based on back propagation of gradient descent is offered to regulate respectively the dc link voltage and the injected cunents in order to overcome the limitations ofthe experimental tuning (Ziegler-Nichols) of the classical PID controller parameters. Simulation results from the system under the Matlab / Simulink environment prove the efficiency of the proposed method and show that the currents injected have the best sinusoidal fonn with a cunent Total Harmonic Distortion of 0.96 % and a net followed of the dc link voltage.