考虑系统频率约束的自适应惯性调整方法

Xibin Wu, Guan Huang, Weijie Cao, Guohua Cui, Wei-Jing Qiu, Yiwu Ge
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引用次数: 0

摘要

随着现代能源系统向清洁能源转型,变流器界面分布式资源的渗透增加,导致惯性和阻尼不足。虚拟同步发电机(VSG)控制通过模拟同步发电的特性,使这些资源能够提供惯性支持。然而,由于惯性分布的不均匀性,系统的惯性需求评估对操作人员来说变得至关重要且具有挑战性。VSG控制的惯性参数难以合理调整。此外,在惯性调节过程中,系统的调节要求,包括频率变化率(RoCoF)和最低点限制,往往被忽略。本文提出了一种考虑系统惯量分布特性的最小系统惯量估计模型,并建立了频率最低点与控制参数之间的关系。同时,设计了一种基于RBF神经网络的惯性调整方法。重要的是,系统的指标约束被集成到惯性调整过程中。以ieee9总线系统为例,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Inertia Adjustment Method Considering System Frequency Constraints
As the modern energy system transitions towards a cleaner one, the penetration of converter-interfaced distributed resources is increased, resulting in the lack of inertia and damping. Virtual synchronous generator (VSG) control enables these resources to provide inertial support by simulating the characteristics of the synchronous generation. However, the inertia requirements evaluation of the system becomes critical yet challenging for the operator due to the uneven distribution of inertia. The inertia parameter of VSG control is difficult to be adjusted appropriately. Also, the regulation requirements of the system, including the rate of change of frequency (RoCoF) and nadir limits, tend to be ignored in the inertia adjustment process. In this paper, we propose a minimum system inertia estimation model considering the distribution characteristics of system inertia and establish the relationship between the frequency nadir and the control parameters. Also, we design an inertia adjustment method based on the RBF neural network. Significantly, the index constraints of the system are integrated into the inertia adjustment process. A case study on IEEE 9 bus system illustrates the effectiveness of the proposed method.
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