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arXiv 1504.04684eess.SYcs.SY
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一种用于电力网络稳定性和韧性的稳健评估框架

A Framework for Robust Assessment of Power Grid Stability and Resiliency

Massachusetts Institute of Technology(麻省理工学院)

Thanh Long Vu, Konstantin Turitsyn

AI总结:

本文提出一种框架,用于构建稳健评估工具,通过数学严谨的证书评估电力网络在功率注入变化和故障源下的稳定性与韧性,采用二次Lyapunov函数方法实现实时稳定性评估。

摘要:

对大规模、强非线性电力网络的安全评估是一个计算成本高的任务。本文提出一种框架,用于构建稳健评估工具,能够提供数学严谨的证书,以评估网络在功率注入变化和故障源下的稳定性与韧性。通过该工具,可以离线筛查多种故障情景或功率注入配置,而无需定期重新评估系统稳定性。特别地,本文提出了两个新的稳健稳定性与韧性评估问题,考虑了平衡点的不确定性以及故障动态的不确定性。此外,本文引入了二次Lyapunov函数方法用于暂态稳定性评估,提供实时的稳定性/韧性证书和实时稳定性评估。所提出技术的有效性在多个IEEE测试案例上进行了数值验证。

英文摘要:

Security assessment of large-scale, strongly nonlinear power grids containing thousands to millions of interacting components is a computationally expensive task. Targeting at reducing the computational cost, this paper introduces a framework for constructing a robust assessment toolbox that can provide mathematically rigorous certificates for the grids' stability in the presence of variations in power injections, and for the grids' ability to withstand a bunch sources of faults. By this toolbox we can "off-line" screen a wide range of contingencies or power injection profiles, without reassessing the system stability on a regular basis. In particular, we formulate and solve two novel robust stability and resiliency assessment problems of power grids subject to the uncertainty in equilibrium points and uncertainty in fault-on dynamics. Furthermore, we bring in the quadratic Lyapunov functions approach to transient stability assessment, offering real-time construction of stability/resiliency certificates and real-time stability assessment. The effectiveness of the proposed techniques is numerically illustrated on a number of IEEE test cases.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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