Online Event-Triggered Switching for Frequency Control in Power Grids With Variable Inertia

IF 7.2 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Power Systems Pub Date : 2025-01-01 DOI:10.1109/TPWRS.2024.3523262
Jie Feng;Wenqi Cui;Jorge Cortés;Yuanyuan Shi
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Abstract

The increasing integration of renewable energy resources into power grids has led to time-varying system inertia and consequent degradation in frequency dynamics. A promising solution to alleviate performance degradation is using power electronics interfaced energy resources, such as renewable generators and battery energy storage for primary frequency control, by adjusting their power output set-points in response to frequency deviations. However, designing a frequency controller under time-varying inertia is challenging. Specifically, the stability or optimality of controllers designed for time-invariant systems can be compromised once applied to a time-varying system. We model the frequency dynamics under time-varying inertia as a nonlinear switching system, where the frequency dynamics under each mode are described by the nonlinear swing equations and different modes represent different inertia levels. We identify a key controller structure, named Neural Proportional-Integral (Neural-PI) controller, that guarantees exponential input-to-state stability for each mode. To further improve performance, we present an online event-triggered switching algorithm to select the most suitable controller from a set of Neural-PI controllers, each optimized for specific inertia levels. Simulations on the IEEE 39-bus system validate the effectiveness of the proposed online switching control method with stability guarantees and optimized performance for frequency control under time-varying inertia.
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变惯量电网频率控制的在线事件触发开关
越来越多的可再生能源并入电网导致了时变系统惯性和随之而来的频率动力学退化。缓解性能下降的一个有希望的解决方案是使用电力电子接口能源,如可再生能源发电机和电池储能系统进行一次频率控制,通过调整其功率输出设定点来响应频率偏差。然而,设计一个时变惯性下的频率控制器是一个挑战。具体来说,针对时不变系统设计的控制器一旦应用于时变系统,其稳定性或最优性就会受到损害。我们将时变惯性下的频率动力学建模为一个非线性开关系统,其中每个模态下的频率动力学用非线性摆动方程描述,不同模态代表不同的惯性水平。我们确定了一个关键的控制器结构,称为神经比例积分(Neural- pi)控制器,它保证了每个模式的指数输入到状态稳定性。为了进一步提高性能,我们提出了一种在线事件触发切换算法,从一组针对特定惯性水平进行优化的Neural-PI控制器中选择最合适的控制器。在IEEE 39总线系统上的仿真验证了所提出的在线开关控制方法的有效性,该方法在时变惯性下具有稳定性保证和优化的频率控制性能。
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来源期刊
IEEE Transactions on Power Systems
IEEE Transactions on Power Systems 工程技术-工程:电子与电气
CiteScore
15.80
自引率
7.60%
发文量
696
审稿时长
3 months
期刊介绍: The scope of IEEE Transactions on Power Systems covers the education, analysis, operation, planning, and economics of electric generation, transmission, and distribution systems for general industrial, commercial, public, and domestic consumption, including the interaction with multi-energy carriers. The focus of this transactions is the power system from a systems viewpoint instead of components of the system. It has five (5) key areas within its scope with several technical topics within each area. These areas are: (1) Power Engineering Education, (2) Power System Analysis, Computing, and Economics, (3) Power System Dynamic Performance, (4) Power System Operations, and (5) Power System Planning and Implementation.
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