This paper proposes a distributed hierarchical cooperative control strategy for a cluster of islanded microgrids (MGs) with intermittent communication, which can regulate the frequency/voltage of all distributed generators (DGs) within each MG as well as ensure the active/reactive power sharing among MGs. A droop-based distributed secondary control scheme and a distributed tertiary control scheme are presented based on the iterative learning mechanics, by which the control inputs are merely updated at the end of each round of iteration, and thus, each DG only needs to share information with its neighbors intermittently in a low-bandwidth communication manner. A two-layer sparse communication network is modeled by pinning one or some DGs (pinned DGs) from the lower network of each MG to constitute an upper network. Under this control framework, the tertiary level generates the frequency/voltage references based on the active/reactive power mismatch among MGs while the pinned DGs propagate these references to their neighbors in the secondary level, and the frequency/voltage nominal set points for each DG in the primary level can be finally adjusted based on the frequency/voltage errors. Stability analysis of the two-layer control system is given, and sufficient conditions on the upper bound of the sampling period ratio of the tertiary layer to the secondary layer are also derived. The proposed controllers are distributed, and thus, allow different numbers of heterogeneous DGs in each MG. The effectiveness of the proposed control methodology is verified by the simulation of an ac MG cluster in Simulink/SimPower Systems.

中文翻译：

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使用两层间歇通信网络的孤岛微电网集群的分布式协调


本文提出了一种针对间歇性通信的孤岛微电网（MG）集群的分布式分级协作控制策略，该策略可以调节每个MG内所有分布式发电机（DG）的频率/电压，并确保各MG之间的有功/无功功率共享。 MG。基于迭代学习机制，提出了基于下垂的分布式二级控制方案和分布式三级控制方案，仅在每轮迭代结束时更新控制输入，因此每个DG只需要共享信息以低带宽的方式间歇地与其邻居进行通信。两层稀疏通信网络是通过从每个MG的下层网络中固定一个或部分DG（pinned DG）来构成上层网络来建模的。在此控制框架下，第三级根据 MG 之间的有功/无功功率失配生成频率/电压参考值，而固定 DG 将这些参考值传播到次级级中的邻居，以及每个 DG 的频率/电压标称设定点初级阶段最终可以根据频率/电压误差进行调整。给出了两层控制系统的稳定性分析，推导了第三层与第二层采样周期比上限的充分条件。所提出的控制器是分布式的，因此允许每个 MG 中有不同数量的异构 DG。通过在 Simulink/SimPower Systems 中对交流 MG 集群进行仿真，验证了所提出的控制方法的有效性。