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Nonlinear controller optimization of a power system based on reduced multivariate polynomial model

机译:基于简化多元多项式模型的电力系统非线性控制器优化

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This paper describes the design of a nonlinear controller in a power system by using the reduced multivariate polynomial (RMP) optimization algorithm with the one-shot training property. The RMP model is applied to estimate its Hessian matrix in addition to identifying the trajectory sensitivities obtained from hybrid system modeling for the power system. In this paper, the saturation limiter of the power system stabilizer (PSS), which is an important nonlinear controller to improve low-frequency oscillation damping performance, is tuned optimally by using Hessian matrix estimated by the RMP model. The performance of the optimal output limits determined by the proposed method is evaluated by applying the large disturbance such as a three-phase short circuit to a power system.
机译:本文通过使用具有一次性训练特性的简化多元多项式(RMP)优化算法,描述了电力系统中的非线性控制器的设计。除了确定从电力系统的混合系统建模中获得的轨迹灵敏度之外,RMP模型还用于估计其Hessian矩阵。本文通过使用RMP模型估算的Hessian矩阵对作为稳定重要的非线性控制器的电力系统稳定器(PSS)的饱和限制器进行了优化调整。通过将较大的干扰(例如,三相短路)应用于电力系统,可以评估通过所提出的方法确定的最佳输出极限的性能。

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