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Learning tangent hypersurfaces for fast assessment of transient stability

机译:学习切线超曲面以快速评估瞬态稳定性

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A new direct method for transient security assessment of multimachine power systems is presented. A local approximation of the stability boundary is made by tangent hypersurfaces which are developed from Taylor series expansion of the transient energy function in the state space nearby a certain class of unstable equilibrium points (UEP). Two approaches for an estimation of the stability region are proposed by taking into account the second order coefficients or alternatively, the second and third order coefficients of the hypersurfaces. Results for two representative power systems are described and a comparison is made with the hyperplane method, demonstrating the superiority of the proposed approach and its potential in real power system applications. Artificial neural networks are used to determine the unknown coefficients of the hypersurfaces independently of operating conditions.
机译:提出了一种用于多机电力系统暂态安全评估的直接方法。稳定边界的局部近似是由切面超表面产生的,该切面是由瞬态能量函数在某一类不稳定平衡点(UEP)附近的状态空间中的暂态能量函数的泰勒级数展开形成的。通过考虑超表面的二阶系数或可替代地,考虑到超表面的二阶和三阶系数,提出了两种估计稳定性区域的方法。描述了两个代表性电力系统的结果,并与超平面方法进行了比较,证明了该方法的优越性及其在实际电力系统应用中的潜力。人工神经网络用于独立于操作条件来确定超曲面的未知系数。

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