Development of constant switching frequency model predictive control for DFIG-based wind energy conversion system in standalone and grid connected operation

Abstract

This paper presents a constant switching frequency (CSF) model predictive control (MPC) for a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS) in standalone and grid-connected operations. The system comprises a cascade connection of a rotor side converter (RSC) and a grid side converter (GSC) with a common DC-link. A battery energy storage system (BESS) is also connected to the common DC-link via a bi-directional dc–dc converter (BDDC). The RSC is controlled through CSF-model predictive current control (CSF-MPCC) scheme in both standalone mode (SAM) and grid-connected mode (GCM) of operations. The GSC control employs the CSF-MPCC scheme in grid-connected operation, whereas CSF-model predictive voltage control (CSF-MPVC) scheme is implemented in standalone operation. Moreover, the power balance is achieved by controlling the BDDC using MPCC to discharge or charge the BESS in response to surplus or deficient power generation. The effectiveness of the proposed control approach for DFIG-based WECS in both SAM and GCM is verified through MATLAB-based simulation and experimental results under different dynamic conditions like variable wind velocity changing from 12 m/s to 8 m/s, different grid demands from 3 kW to 1.5 kW and load change of 4 kW to 6.5 kW. Moreover, the robustness of the proposed control is corroborated by parametric sensitivity, time delay, and grid unbalance, along with its low-voltage ride-through (LVRT) capability during an LLLG fault.