The performance of the existing frequency control strategies for MT-HVDC systems relies on the accuracy of the mathematical models. However, it is hard to obtain the exact mathematical models of MT-HVDC systems. To deal with this challenge, this paper presents a distributed cooperative frequency control strategy for MT-HVDC systems by using a reinforcement learning method, i.e., value iteration algorithm. Specifically, the proposed control strategy is data driven and hence model free. Besides, the proposed control strategy is distributed in the sense that each AC area only requires the local and neighboring information, rather than the information of all the AC areas. Moreover, the proposed control strategy makes the connected AC areas compensate load disturbances together by sharing their power reserves via HVDC grids, which greatly decreases the operation costs of MT-HVDC systems. The performance of the proposed control strategy is validated by cases study.

MT-HVDC 系统现有频率控制策略的性能依赖于数学模型的准确性。然而，很难获得MT-HVDC系统的精确数学模型。为应对这一挑战，本文提出了一种用于MT-HVDC 系统的分布式协作频率控制策略，采用强化学习方法，即值迭代算法。具体来说，所提出的控制策略是数据驱动的，因此是无模型的。此外，所提出的控制策略是分布式的，即每个 AC 区域只需要本地和相邻信息，而不是所有 AC 区域的信息。此外，所提出的控制策略使连接的交流区域通过 HVDC 电网共享其功率储备来共同补偿负载扰动，大大降低了MT-HVDC系统的运行成本。通过案例研究验证了所提出的控制策略的性能。