A Universal Model Predictive Control of DFIG in the Wind Solar Hybrid System

Abstract

Hybrid Systems are the future of power generation. Together, they can make up for the inefficiency of one and give more effective result, as in the case of wind and solar generation. Double Fed Induction Generators (DFIG) are mainly used for Wind Energy Conversion because of the generation during variable wind speeds. There are two Voltage Source Converters (VSC) on the machine side and grid side of the Wind Energy Conversion System (WECS). A Solar Photo Voltaic System (SPVS) with a boost converter is equipped with an incremental conductance maximum power point tracking algorithm (MPPT). The conventional vector control suffers from complex decoupling processes, computational complexity, and slow dynamic response. To address these issues, this work presents Model Predictive Power Control (MPPC) to improve performance while reducing power ripples, current distortion, computation, and system complexity. The performance analysis is conducted for both vector control and MPPC by implementing the simulation model in MATLAB/SIMUINK. The performance of the PV system under different irradiances is carried out. THD analysis is carried out for MPDPC.