Flywheel Motor Control Based on Improved Direct Current Model Prediction Control Method

With the growing proportion of new energy power generation, the stability of power grid operation is facing great challenges. As a form of mechanical energy storage, flywheel energy storage can improve the frequency and peak regulation ability of power grid. In this paper, an Improved Direct Current Model Predictive Control(IDC-MPC) method is proposed to enhance the control performance of flywheel motors. The cost function of IDC-MPC has been improved by adding a switching frequency term, and a decision model is consequently constructed using the Analytic Hierarchy Process, allowing for the calculation of various weights. By synthesizing two adjacent basic voltage vectors into extended voltage vectors, the voltage vector set of IDC-MPC is improved, thereby enhancing the precision of motor control. A stepwise optimization method for voltage vector selection is proposed to reduce the number of voltage vector selection iterations of IDC-MPC and reduce system computational complexity simultaneously. Finally, the proposed method is simulated and verified, and further compared with PI control and direct current predictive control to demonstrate its feasibility and superiority.