Adaptive distributed MPC based load frequency control with dynamic virtual inertia of offshore wind farms

Xiao Qi, Lingyao Lei, Changhui Yu, Zekai Ma, Taotao Qu, Ming Du, Miaosong Gu
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Abstract

The penetration of offshore wind farms (OWFs) in city‐close power systems is rapidly increasing. System inertia will be further reduced. Active frequency support of wind power is essential to solve the load frequency control (LFC) problem. Here, the dynamic virtual inertia control (VIC) method is employed to enhance frequency stability within the permitted operating states of OWFs. An adaptive distributed model predictive control (DMPC) method is proposed and applied to an interconnected power system. The dynamic VIC‐based LFC model is derived and used to construct the predictive model of DMPC. To expand the adaptation of the analytical linearized model of OWFs in different operating points, the adaptive law is further designed to dynamically adjust the parameters of DMPC. The simulation results demonstrate the effectiveness of the proposed control method. The frequency fluctuations can be well‐restrained under different disturbances.
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基于分布式 MPC 的自适应负载频率控制与海上风电场的动态虚拟惯性
海上风电场(OWFs)在城市近距离电力系统中的渗透率正在迅速提高。系统惯性将进一步降低。风电的有功频率支持对解决负载频率控制(LFC)问题至关重要。在此,我们采用动态虚拟惯性控制(VIC)方法,在风力发电机允许的运行状态下提高频率稳定性。本文提出了一种自适应分布式模型预测控制(DMPC)方法,并将其应用于互联电力系统。推导出了基于 VIC 的动态 LFC 模型,并将其用于构建 DMPC 的预测模型。 为了扩大 OWF 分析线性化模型在不同运行点的适应性,进一步设计了自适应法则,以动态调整 DMPC 的参数。 仿真结果证明了所提控制方法的有效性。在不同的干扰下,频率波动都能得到很好的抑制。
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