提高低惯量电力系统频率安全性的快速频响储备的确定

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS
Savvas Panagi , Petros Aristidou
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引用次数: 0

摘要

可再生能源在电网中的日益普及已导致传统发电机逐渐退役,从而导致可用惯性和其他频率支持储备的减少。因此,电力系统,特别是孤岛式低惯性电力系统的频率安全性受到损害,导致干扰后的频率偏差更快,更极端。迫切需要采用更快的频率储备,以稳定系统并增强其弹性和可靠性。本文首先研究了低惯量电网中各种频率支撑机制对系统频率安全性的影响。然后,我们提出了一种新颖的、数据驱动的、基于梯度下降的方法,该方法将动态安全评估(DSA)与线性预测相结合,以优化低惯性网格的快速频率响应(FFR)尺寸。使用塞浦路斯500个选定的历史操作场景的动态模型评估了所提议方法的性能。结果表明,该算法收敛速度快,以最小的计算量达到目标频率的最低点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Sizing of Fast Frequency Response Reserves for improving frequency security in low-inertia power systems

Sizing of Fast Frequency Response Reserves for improving frequency security in low-inertia power systems
The increasing penetration of Renewable Energy Sources (RES) in electricity grids has led to the gradual decommissioning of conventional generators and, thus, to a decrease in the available inertia and other frequency support reserves. Consequently, the frequency security of power systems, in particular islanded low-inertia ones, is compromised, leading to faster and more extreme frequency deviations following disturbances. There is an urgent need to incorporate faster frequency reserves that can stabilize the system and enhance its resilience and reliability. This paper first investigates the impact of various frequency support mechanisms on the system frequency security in low-inertia grids. Then, we propose a novel, data-driven, gradient-descent-based method, that combines Dynamic Security Assessment (DSA) with linear predictions to optimize Fast Frequency Response (FFR) sizing for low-inertia grids. The performance of the proposed approach is evaluated using the dynamic model of Cyprus across 500 selected historical operating scenarios. The results demonstrate fast convergence, achieving the target frequency Nadir with minimal computational effort.
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来源期刊
Sustainable Energy Grids & Networks
Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology
CiteScore
7.90
自引率
13.00%
发文量
206
审稿时长
49 days
期刊介绍: Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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