A Data-Driven Energy Storage System-Based Algorithm for Monitoring the Small-Signal Stability of Power Grids with Volatile Wind Power

被引：0
作者：
Zenelis, Ilias [1 ]
Pierrou, Georgia [1 ]
Wang, Xiaozhe [1 ]
机构：
[1] McGill Univ, Dept Elect & Comp Engn, Montreal, PQ H3A 2K6, Canada
来源：
2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM) | 2021年
基金：
加拿大自然科学与工程研究理事会;
关键词：
Data-driven methods; energy storage systems; small-signal stability monitoring; wind power; AREA DAMPING CONTROL;
D O I：
10.1109/PESGM46819.2021.9638004
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
In this paper, we propose a data-driven energy storage system (ESS)-based method to enhance the online small-signal stability monitoring of power networks with high penetration of intermittent wind power. To accurately estimate inter-area modes that are closely related to the system's inherent stability characteristics, a novel algorithm that leverages on recent advances in wide-area measurement systems (WAMSs) and ESS technologies is developed. It is shown that the proposed approach can smooth the wind power fluctuations in near real-time using a small additional ESS capacity and thus significantly enhance the monitoring of small-signal stability. Dynamic Monte Carlo simulations on the IEEE 68-bus system are used to illustrate the effectiveness of the proposed algorithm in smoothing wind power and estimating the inter-area mode statistical properties.
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页数：5
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