Load- and Renewable-Following Control of Linearization-Free Differential Algebraic Equation Power System Models
Load- and Renewable-Following Control of Linearization-Free Differential Algebraic Equation Power System Models
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DOI：
10.1109/tcst.2023.3244492
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发表时间：
2021-04
影响因子：
4.8
通讯作者：
Sebastian A. Nugroho;A. Taha
中科院分区：
文献类型：
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作者：
Sebastian A. Nugroho;A. Taha
电力网络中的机电暂态主要是由电力消耗和生产之间的不匹配引起的，导致发电机偏离标称频率。为此，反馈控制算法已被设计为执行频率和负载/可再生跟随控制。特别地，文献解决了过多的电网和频率控制挑战，重点是线性化的微分方程模型，其中代数约束[即，功率流（PF）]被消除。这与更现实的非线性微分代数方程（NDAE）模型相反。然而，随着电网越来越多地通过间歇性可再生能源和变化的负载被推到其极限，由于可再生能源或需求的预测不佳或突然变化，它们的物理状态有可能逃离操作区域，从而认为基于线性化点的反馈控制器实际上是不可用的。代替线性化的微分方程模型，本文的目标是设计一个简单的，纯粹分散的，线性化的，反馈控制律的NDAE模型的电力网络。这种控制器的目的是在可再生能源或负载中的显著未知干扰之后主要稳定频率振荡。虽然控制器的设计涉及先进的NDAE系统理论，控制器本身是一样简单的分散比例或线性二次型调节器（LQR）在其实施。算例表明，所设计的控制器能够在较大扰动下稳定系统的动态和代数状态。
Electromechanical transients in power networks are mostly caused by a mismatch between power consumption and production, causing generators to deviate from the nominal frequency. To that end, feedback control algorithms have been designed to perform frequency and load/renewable-following control. In particular, the literature addressed a plethora of grid- and frequency-control challenges with a focus on linearized, differential equation models whereby algebraic constraints [i.e., power flows (PFs)] are eliminated. This is in contrast to the more realistic nonlinear differential algebraic equation (NDAE) models. Yet, as grids are increasingly pushed to their limits via intermittent renewables and varying loads, their physical states risk escaping operating regions due to either a poor prediction or sudden changes in renewables or demands—deeming a feedback controller based on a linearization point virtually unusable. In lieu of linearized differential equation models, the objective of this article is to design a simple, purely decentralized, linearization-free, feedback control law for the NDAE models of power networks. The aim of such a controller is to primarily stabilize frequency oscillations after a significant, unknown disturbance in renewables or loads. Although the controller design involves advanced NDAE system theory, the controller itself is as simple as a decentralized proportional or linear quadratic regulator (LQR) in its implementation. Case studies demonstrate that the proposed controller is able to stabilize dynamic and algebraic states under significant disturbances.