Experimental investigation of predictive control for PMSM-based wind turbine generation system

Abstract

The theoretical analysis of permanent magnet synchronous machine (PMSM)-based wind turbine generation system was presented by many researchers; nevertheless, although the practical setup is still quite difficult, it is more valid. Moreover, the main challenge facing wind power systems is figuring out how to extract the most energy from varying wind speeds. Since wind turbine maintenance is hard and expensive, using wind speed sensors is a challenging operation. Therefore, this research suggests an effective and practical control system based on the Model Predictive Control Scheme (MPCS) for both the grid-side converter (GSC) and the machine-side converter (MSC) to optimize power extraction from wind energy. Detailed exploration of the MPCS for the PMSM and predictive power control (PPC) for the GSC involves stages such as flux estimation, torque prediction, and cost function minimization. The results obtained validate the higher performance of MPCS in comparison to the direct torque control (DTC) method. Furthermore, excellent tracking with high accuracy is achieved in relation to simulation and experimental data. Additionally, an evaluation indices based on root mean square error (RMSE) and gross system efficiency are used for wind turbine performance. These indices are used to show that, the feasibility of the MPCS approach compared with DTC under the same WT conditions. This approach offers a promising avenue for cost-effective wind energy conversion. The control systems were designed and implemented utilizing a DSPACE 1104 card. Experimental results confirm the effectiveness of the proposed mechanism in achieving maximum power point tracking (MPPT).