基于智能自学习控制的船舶微电网预同步控制策略

针对船舶靠港期间微电网并网预同步控制过程的频率偏移越限问题，提出一种基于智能自学习控制的船舶微电网预同步控制策略。首先，通过利用已知虚拟同步发电机输出相角计算船舶微电网与船舶主电网之间的相位差。然后，基于改进的动态线性化方法将离散后相位差非线性系统转化为紧格式局部线性化数据模型。之后，根据数据模型设计智能自学习虚拟同步发电机预同步控制算法。最后，通过船舶虚拟同步发电机预同步过程中功频下垂系数的自适应调整避免船舶微电网输出频率的偏移越限。通过对比仿真实验，所提控制策略可实现快速平滑的并网预同步控制并有效规避了频率越限，实现了船舶本地异步电机负载的正常稳定工作，验证了该控制策略应用于靠港船舶微电网的优越性和精确性。

Pre-synchronization control strategy for a microgrid of merchant marine with intelligent self-learning control

There can be frequency out-of-limit caused by the pre-synchronization control of the microgrid during ship berthing. Thus this paper proposes a pre-synchronization control strategy for a ship microgrid based on intelligent self-learning control. First, the phase difference between the ship microgrid and the main grid is calculated by using the phase angle of a virtual synchronous generator. Then, based on an improved dynamic linearization method, the discrete phase difference nonlinear system is transformed into a compact linearized data model. The intelligent self-learning virtual synchronous generator pre-synchronization control algorithm is designed according to the data model. Finally, the adaptive adjustment of the power frequency droop coefficient of the generator is designed to avoid the frequency out-of-limit during the pre-synchronization process. The proposed control strategy realizes smooth grid-connected pre-synchronization control and effectively avoids the frequency out-of-limit by comparison simulation. This ensures the stable operation of the asynchronous motor load. The proposed control strategy demonstrates its superiority and accuracy when applied to the ship microgrid.