基于改进直接电流模型预测方法的飞轮电机控制

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

  • 摘要: 随着新能源发电比重越来越大,电网运行稳定性面临巨大挑战,飞轮储能作为机械储能的一种,可以增强电网的调频调峰能力。提出一种改进直接电流模型预测控制方法提升飞轮电机的控制性能。通过加入开关次数项改进了直接电流模型预测控制的代价函数,利用层次分析法构建了决策模型并计算各项权重;通过将两相邻基本电压矢量合成为扩充电压矢量,改进了直接电流模型预测控制电压矢量集,提高了电机控制的精度;提出了电压矢量选择分步优化方法,用以减少直接电流模型预测控制的电压矢量选择遍历次数,降低了系统计算量。最后对所提方法进行仿真验证,并与PI矢量控制、直接电流模型预测控制方法进行对比分析,验证了所提方法的可行性与优越性。

     

    Abstract: 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.

     

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