This article presents a distributed model predictive control algorithm for power flow systems that can maintain overall stability when the system equilibrium configuration changes. The dynamics of the large‐scale power flow systems can be described by transportation, conversion, and storage of energy among and across subsystems. By strategically choosing the output for each subsystem and augmenting each local model predictive controller with a special passivity‐incremental constraint, the equilibrium‐independent dissipativity property of each closed‐loop subsystem can be guaranteed. The dissipativity‐preserving coupling between subsystems in the power flow system can be utilized to maintain equilibrium‐independent dissipativity and stability of the overall system. Simulation results of a fluid tank system with a changing equilibrium configuration show the effectiveness of the proposed algorithm.

中文翻译：

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保证具有独立于平衡的稳定性的潮流系统的基于耗散性的模型预测控制算法

本文提出了一种用于潮流系统的分布式模型预测控制算法，该算法可以在系统平衡配置发生变化时保持整体稳定性。大型潮流系统的动力学可以通过子系统之间以及子系统之间的能量传输，转换和存储来描述。通过策略性地选择每个子系统的输出并通过特殊的无源增量约束来扩充每个局部模型预测控制器，可以确保每个闭环子系统的平衡无关耗散特性。潮流系统中子系统之间的保持耗散性耦合可用于维持整个系统的独立于平衡的耗散性和稳定性。