利用电力系统状态还原模型的 DA 估算电网故障的关键清除时间

IF 6.9 2区 工程技术 Q2 ENERGY & FUELS CSEE Journal of Power and Energy Systems Pub Date : 2023-11-17 DOI:10.17775/CSEEJPES.2022.07170
Yang Liu;Zhongyang Chen;Huanjin Yao;Lin Yi;Q. H. Wu
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引用次数: 0

摘要

本文通过电力系统状态还原模型的吸引域(DA),利用平方和(SOS)编程法提出了一种临界清除时间(CCT)估算方法。利用雅各布矩阵的性质和吸引域边界的结构,发现状态还原模型的吸引域和电力系统完整模型的吸引域是拓扑同构的。两个系统模型的平衡点数量、平衡点类型和解之间存在一一对应关系。基于这些发现,提出了一种利用 SOS 编程估计状态还原模型 DA 的扩展内部算法。完整模型的状态轨迹可以通过正交或等半径投影转换为状态还原模型的轨迹。这样,网格故障的 CCT 就可以通过状态还原模型的 DA 进行估算。与使用完整模型相比,使用状态还原模型估算 DA 时的 SOS 编程计算负担较小。仿真结果表明,所提出的扩展内部算法能够以更高的精度和更低的时间成本提供电力系统 DA 的精确估算。
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Estimating Critical Clearing Time of Grid Faults Using DA of State-Reduction Model of Power Systems
This paper proposes a critical clearing time (CCT) estimation method by the domain of attraction (DA) of a state-reduction model of power systems using sum of squares (SOS) programming. By exploiting the property of the Jacobian matrix and the structure of the boundary of the DA, it is found the DA of the state-reduction model and that of the full model of a power system are topological isomorphism. There are one-to-one correspondence relationships between the number of equilibrium points, the type of equilibrium points, and solutions of the two system models. Based on these findings, an expanding interior algorithm is proposed with SOS programming to estimate the DA of the state-reduction model. State trajectories of the full model can be transformed to those of the state-reduction model by orthogonal or equiradius projection. In this way, CCT of a grid fault is estimated with the DA of the state-reduction model. The calculational burden of SOS programming in the DA estimation using the state-reduction model is rather small compared with using the full model. Simulation results show the proposed expanding interior algorithm is able to provide a tight estimation of DA of power systems with higher accuracy and lower time costs.
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来源期刊
CiteScore
11.80
自引率
12.70%
发文量
389
审稿时长
26 weeks
期刊介绍: The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.
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