Stabilization Improvement of MPC based DC-DC Converter with Load Estimation
Stabilization Improvement of MPC based DC-DC Converter with Load Estimation
复制标题
基于 MPC 的具有负载估计的 DC-DC 转换器的稳定性改进
DOI：
10.1109/icrera49962.2020.9242837
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Maruta Hidenori
中科院分区：
文献类型：
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作者：
Umeno Naoto;Maruta Hidenori
近年来，全球对可再生能源的需求正在迅速增加，因为它可以为能源消耗和全球变暖提供解决方案之一。然而，存在由诸如天气条件、地理因素等引起的来自可再生能源电源的电力输出的不稳定的能量波动的问题。为了抑制这种功率波动，功率转换器的模型预测控制具有实现上级稳定的潜力，因为控制方法是基于转换器系统的模型及其预测值的。在本文中，我们考虑的方法，提高了稳定性的传统模型预测控制，通过使用负载估计，提高了控制中使用的模型的精度。此外，模型预测控制与卡尔曼滤波器相结合，采用，以减少噪声观测数据的影响。我们评估我们提出的方法，揭示它具有上级性能相比，传统的方法在模拟研究。
Recently, the worldwide demand for renewable energy is rapidly increasing since it can provide one of the solutions for energy consumption and global warming. However, there is a problem of unstable energy fluctuation of electric power output from renewable energy power sources caused by such as weather conditions, geographical factors, and so forth. To suppress such power fluctuation, a model predictive control of power converters has the potential to achieve superior stabilization since the control method is based on the model of the converter system and its predicted values. In this paper, we consider a method that improves the stability of the conventional model predictive control by using a load estimation which improves the accuracy of the model used in the control. Also, the model predictive control is combined with a Kalman filter which is adopted to reduce the effect of noisy observed data. We evaluate our proposed method to reveal it has a superior performance compared to the conventional method in the simulation study.