Wave energy is a renewable energy with a high density. There are different types of wave power generation systems (WPGSs), including Archimedes wave swing (AWS) coupled to a linear permanent magnet synchronous generator. This study proposes a model predictive control (MPC) for AWS‐based WPGS. The predictive current controller is implemented in a generator‐side converter as a substation for proportional integral (PI) controllers with pulse‐width modulation (PWM). Also, a supercapacitor energy storage system with bidirectional DC/DC converter is proposed to maintain DC link voltage stability. A DC/DC converter is used to keep DC microgrid bus voltage at the desired value. The effectiveness of the proposed MPC method is tested at various operating conditions and compared with conventional PI controllers with PWM in the MATLAB/SIMULINK environment.

中文翻译：

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通过直流电缆连接到直流微电网的直接驱动波发电系统的模型预测控制

波浪能是高密度的可再生能源。存在多种类型的波浪发电系统（WPGS），包括与线性永磁同步发电机耦合的阿基米德波浪摆动（AWS）。这项研究提出了基于AWS的WPGS的模型预测控制（MPC）。预测电流控制器在发电机侧的转换器中实现，作为带有脉宽调制（PWM）的比例积分（PI）控制器的变电站。此外，提出了一种具有双向DC / DC转换器的超级电容器储能系统，以保持DC链路电压的稳定性。DC / DC转换器用于将DC微电网总线电压保持在所需值。所提出的MPC方法的有效性在各种操作条件下进行了测试，并与MATLAB / SIMULINK环境中具有PWM的传统PI控制器进行了比较。