Fast DC-link voltage control based on power flow management using linear ADRC combined with hybrid salp particle swarm algorithm for PV/wind energy conversion system

Hybrid Energy Systems (HESs) are offering several advantages over conventional generation systems because of the rising need for Renewable Energy Resources (RERs) and its high capability and flexibility of achieving the desired performance for both urban and rural areas. The main goals of HESs are to improve the system performance by increasing its flexibility, reliability and reducing generation instability. In the current work, a hybrid Photovoltaic/Wind Energy Conversion System (PV/WECS) is proposed to supply and support the utility grid. The generated power from the system is greatly responding to the change in both the wind speed and PV irradiance level, and as a result impacting the DC-Bus voltage of the system converters. Therefore, precise, fast and optimum controllers are required for the PV/WECS system to ensure the extraction and generation of stable maximum power during weather variations along with maintaining the DC-Link voltage at the desired value. Further, this study proposes a novel Linear Active Disturbance Rejection Control (LADRC) combined with a hybrid Salp Particle Swarm Algorithm (SPSA) to a grid-connected PV/WECS for extracting the Global Maximum Power (GMP), regulating the DC-Link voltage, and enhancing the active and reactive powers control. The capability of the proposed SPSA-LADRC based-MPPT approach is examined according to the tracking time, accuracy and response to internal and external disturbances and then comparing its performance with other techniques such as SPSA-SMC, SPSA-PID and SPSA-PI controllers respectively. The findings revealed that the LADRC can track and keep the DC-Link voltage as the desired reference value,1500 V, respond much faster than the PI, SMC, and PID controllers as well as keep the THD of the injected current into the grid at a low level of 2.25%. Finally, the performance of the proposed system is experimentally verified using Hardware-In-Loop (HIL). The obtained findings verify the capability and accuracy of the system and its great potential in the management of HESs.