Dynamic Modeling and Robust Control by ADRC of Grid-Connected Hybrid PV-Wind Energy Conversion System

This work presents linear and nonlinear control strategies applied to a grid-connected multiple-source renewable energy system (wind and photovoltaic), in order to extract the maximum power and to enhance the control of the active and reactive powers. A new robust control strategy known as the active disturbance rejection control (ADRC) is proposed and applied to the hybrid renewable energy system (HRES), and it is based on the extended state observer (ESO) which allows us to estimate the internal and external disturbances such as modeling errors and parameter variations. The studied system consists of two conversion chains which are linked via a common DC bus and interconnected to the grid through a voltage source inverter (VSI); the first chain consists of a PV system and a DC-DC boost converter, and the second chain consists of a direct-driven wind turbine, permanent magnetic synchronous generator (PMSG), and of a AC/DC rectifier converter. The extraction of maximum power from the PV system and the wind energy conversion system is ensured by using the voltage based perturb and observe (VPO) and the optimal torque control (OTC) MPPT techniques, respectively. The ADRC technique is utilized to control the active and reactive powers by acting on the grid currents. In order to verify and validate the effectiveness of the proposed control strategy, a detailed model of the studied system is designed and evaluated under the MATLAB/Simulink software. The simulation results prove the effectiveness of the MPPT techniques in terms of maximum power extraction during the variation in the environmental conditions. Additionally, the regulation of active and reactive powers is ensured by ADRC, and the system is operating at a unity power factor. Moreover, it is demonstrated that the suggested strategy is efficient in terms of fast tracking and robustness to internal and external disturbances compared to the classical PI controller.