A Method for Power System Static Stability Situation Assessment Based on Scale Invariant Feature Transform

2018 International Conference on Power System Technology (POWERCON) Pub Date : 2018-11-01 DOI:10.1109/POWERCON.2018.8601789

Yi Tian, Gan-gui Yan, Dao-wei Liu, Baixue Li, Rui Zhang, Hongying Yang, Gao-shang Zhao

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引用次数: 1

Abstract

Power system static stability situation assessment is the core of power system security prevention and control. Most of traditional static stability assessment methods are focused on physical models and high-intensity simulations. These methods have a large amount of calculation and high dimensionality, and its online engineering applicability cannot be guaranteed. In order to better ensure the safe operation of power system, this paper proposes a static stability assessment method based on scale-invariant feature transformation(SIFT). This method directly extracts the association of holographic data under various static operating conditions of power system. Based on the operating feature it is improved for the generalized elasticity index and it is achieved for an accurate assessment of static stability situation. The simulation result of the New England 10-machine 39-bus system indicates that the improved grid generalized elasticity index has a higher slope and better engineering application value.

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基于尺度不变特征变换的电力系统静态稳定状态评估方法

电力系统静稳定态势评估是电力系统安全防控的核心。传统的静态稳定性评估方法大多集中在物理模型和高强度模拟上。这些方法计算量大、维数高，无法保证其在线工程适用性。为了更好地保证电力系统的安全运行，本文提出了一种基于尺度不变特征变换(SIFT)的电力系统静态稳定性评估方法。该方法直接提取了电力系统各种静态运行条件下全息数据的关联关系。根据其运行特点，对广义弹性指标进行了改进，实现了对静稳定状况的准确评价。新英格兰10机39总线系统的仿真结果表明，改进后的网格广义弹性指数具有较高的斜率和较好的工程应用价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2018 International Conference on Power System Technology (POWERCON)

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