基于大规模逆变器资源的容错分散控制以实现有功功率跟踪
Fault-Tolerant Decentralized Control for Large-scale Inverter-based Resources for Active Power Tracking
AI总结：
本文提出一种基于原始-对偶的分散式分层容错控制框架，通过底层电流控制与高层自适应功率分配，在考虑线路健康状态下实现IBRs有功功率跟踪，显著降低了故障条件下的功率偏差与调节时间。
摘要：
并网逆变器资源（IBRs）缺乏传统同步发电机（SG）所具有的惯量响应等内在特性，其接入在分析电网稳定性方面带来了新的挑战。尽管IBRs的动态构成与SGs不同，但控制目标在跟踪期望有功功率方面保持相似。本文提出了一种基于原始-对偶的分散式容错控制框架，用于IBRs中的功率分配。总体而言，开发了一种分层控制算法，底层负责IBRs的电流控制和参数估计，高层则根据期望的有功功率曲线作为底层的参考功率生成器。该基于网络的分散式算法在考虑IBRs传输线路健康状况的情况下，自适应地在IBRs之间分配期望功率。所提框架通过在IBRs网络上的仿真进行了测试，并将高层控制器的性能与文献中现有框架进行了比较。结果表明，在故障条件下，与文献中的算法相比，所提算法在功率偏差幅度和稳定至标称值的调节时间上均表现出显著的性能提升。
英文摘要：
Integration of Inverter Based Resources (IBRs) which lack the intrinsic characteristics such as the inertial response of the traditional synchronous-generator (SG) based sources presents a new challenge in the form of analyzing the grid stability under their presence. While the dynamic composition of IBRs differs from that of the SGs, the control objective remains similar in terms of tracking the desired active power. This letter presents a decentralized primal-dual-based fault-tolerant control framework for the power allocation in IBRs. Overall, a hierarchical control algorithm is developed with a lower level addressing the current control and the parameter estimation for the IBRs and the higher level acting as the reference power generator to the low level based on the desired active power profile. The decentralized network-based algorithm adaptively splits the desired power between the IBRs taking into consideration the health of the IBRs transmission lines. The proposed framework is tested through a simulation on the network of IBRs and the high-level controller performance is compared against the existing framework in the literature. The proposed algorithm shows significant performance improvement in the magnitude of power deviation and settling time to the nominal value under faulty conditions as compared to the algorithm in the literature.
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