This paper proposes the new high-gain observer dedicated to the SEPIC converter and the single-phase inverter. The high-gain observer is designed in order to minimize the number of sensors required, because the use of voltage and current sensors have many disadvantages. In fact, these sensors can obtain a bulky system, also, they are expensive and take up more place. Also, this paper proposes new controller able to locate and track the global maximum power point under the partial shading effect. Actually, when the partial shading occurs, the Power-Voltage curve presents more than one maximum power point, which are divided between the global maximum and the local maximums. The global maximum presents the superior one, while the local maximums present the inferior ones. The classical methods like Perturb and Observe and Incremental Conductance are no longer able to distinguish the global maximum point. So, they cause a high drop of power, which justifies the need of a controller that can solve such problems. Effectively, the proposed controller is designed for this purpose, it consists of an algorithm able to locate the global maximum power point and generate the reference input of corresponding voltage. Also, this controller consists of the sliding mode controller that is able to track the reference input by acting on the SEPIC converter's duty cycle. In addition, the SEPIC converter is connected to the grid through the single-phase inverter. However, to make this connection, it should unify the power factor and synchronize the inverter current with the grid voltage. Effectively, these two tasks are solved by designing the sliding mode controller that acts on the inverter duty-cycle to allow its current to be in the same shape and phase as the grid voltage. Also, the DC bus voltage is regulated by using the PI controller. The overall system is modelled mathematically, tested and validated under Matlab/Simulink environment to show the criteria's performances and efficiency improvement of PV panel by using the proposed Global Maximum Power Point Tracking controller. Moreover, the proposed controller is compared with the hybrid controllers: P&Osliding mode, IC-sliding mode and PSO-Backstepping controllers. The results illustrate the performance of the proposed controlled to distinguish and track rapidly (about 40ms depending on the shading pattern), and accurately the desired global maximum power point.
The temperature and radiation changes lead to obvious fluctuations in photovoltaic panels ' output power. To optimally exploit the PV system, maximum power point tracking (MPPT) is needed. Various offline and online methods for monitoring the MPP have been implemented. In this work, a maximum power point tracking (MPPT) technique was created which is primarily based on backstepping integral sliding mode controller (BISMC) design. The control scheme incorporates two parts: the first is based on an artificial neural network that provides the reference voltage, that supplies the maximum power regardless the environmental factors, which is given to the proposed BISMC control that is responsible on regulation of the duty cycle of the DC-DC boost converter's PWM applied switch (Mosfet). This strategy offers very low tracking error, and chattering improvement in tracking the MPP of a PV system when the environmental disturbances occur. The added integral action is very important in the control closed loop because it removes the steady state error. The method is compared with the ANN-sliding mode, PSO-backstepping and P&O-backstepping controllers in order to demonstrate its efficiency. In this later, the P&O (perturb & observe) and the PSO (particle swarm optimization) algorithms serve to generate reference voltage, that corresponds to the MPP, while the backstepping controller tracks this reference voltage. To reduce the PV system cost, a high-gain observer is designed, it requires only the PV output voltage sensor which enables the unmeasured PV system state variables online. This allows the minimization of the number of sensors in practical case because they have many disadvantages. The use of these sensors can lead to bulky system. Moreover, they are expensive. The simulation study is carried out under Matlab/Simulink. The results of the suggested MPPT reveal outstanding dynamic response under rapid changes of irradiation and temperature. The suggested method is more accurate and has fast convergence time about 2.2 ms and 1ms depends on the meteorological condition changes and 98% of efficiency to track the maximum power point.
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