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Available Transfer Capability Calculation Constrained with Small-Signal Stability Based on Adaptive Gradient Sampling

机译:可用于基于自适应梯度采样的小信号稳定性计算的可用传输能力计算

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Due to the nonsmoothness of the small-signal stability constraint, calculating the available transfer capability (ATC) limited by small-signal stability rigorously through the nonlinear programming is quite difficult. To tackle this challenge, this paper proposes a sequential quadratic programming (SQP) method combined with gradient sampling (GS) in a dual formulation. The highlighted feature is the sample size of the gradient changes dynamically in every iteration, yielding an adaptive gradient sampling (AGS) process. Thus, the computing efficiency is greatly improved owing to the decrease and the parallelization of gradient evaluation, which dominates the computing time of the whole algorithm. Simulations on an IEEE 10-machine 39-bus system and an IEEE 54-machine 118-bus system prove the effectiveness and high efficiency of the proposed method.
机译:由于小信号稳定性约束的非现状,计算通过非线性编程严格地通过非线性编程来限制的可用传输能力(ATC)非常困难。为了解决这一挑战,本文提出了一种与双制剂中的梯度采样(GS)结合的顺序二次编程(SQP)方法。突出显示的特征是在每次迭代中动态地发生梯度变化的样本大小,产生自适应梯度采样(AGS)过程。因此,由于梯度评估的降低和平行化,从而大大提高了计算效率,其主导了整个算法的计算时间。 IEEE 10机器39总线系统的模拟和IEEE 54机器118总线系统证明了所提出的方法的有效性和高效率。

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