摘要
为减轻振荡对新能源电力系统的冲击,有必要在线评估系统稳定状态并定位系统振荡薄弱点,提前采取措施。为此,分别从端口频域特性和时域响应角度提出两种新能源电力系统振荡薄弱点定位方法。频域方法基于新能源场站端口阻抗特性评估系统稳定状态,并根据各新能源场站端口阻抗实部的大小定位薄弱场站。时域方法通过主动注入宽频小扰动信号,利用HHT(希尔伯特-黄变换)分析各新能源场站端口电流响应,提取薄弱模态的阻尼比,根据阻尼比大小定位薄弱场站。以三个风电场构成的小型新能源系统为例,对上述两种定位方法的有效性进行验证,结果表明两种方法均能准确定位系统振荡的薄弱点。
To mitigate the impact of oscillations on new energy power systems,it is crucial to assess the system stability state online and identify weak points susceptible to oscillations for proactive measures.To achieve this,two methods for locating weak points in new energy power systems are proposed,each from the perspectives of frequency domain characteristics and time-domain responses of the ports.The frequency domain method involves evaluating the system's stability state based on the impedance characteristics of the ports at new energy substations,pinpointing weak substations according to the magnitude of the real part of the impedance at each substation.The timedomain method involves actively injecting a wideband small disturbance signal and utilizing the HHT(HilbertHuang transform) to analyze the current response at each port of new energy substations.Damping ratios of weak modes are extracted,and weak substations are located based on their magnitudes.The effectiveness of these location methods is validated using a small-scale new energy system composed of three wind farms.The results indicate that both methods accurately identify weak points in the system oscillations.
作者
马骏超
高磊
陈晓刚
吕敬
彭琰
王晨旭
刘佳宁
MA Junchao;GAO Lei;CHEN Xiaogang;LYU Jing;PENG Yan;WANG Chenxu;LIU Jianing(State Grid Zhejiang Electric Power Co.,Ltd.Research Institute,Hangzhou 310014,China;Key Laboratory of Control of Power Transmission and Conversion,Ministry of Education(Shanghai Jiao Tong University),Shanghai 200240,China;State Grid Zhejiang Electric Power Co.,Ltd.,Hangzhou 310007,China)
出处
《浙江电力》
2024年第3期1-7,共7页
Zhejiang Electric Power
基金
国网浙江省电力有限公司科技项目(B311DS22000K)
国家自然科学基金项目(52277195)。
关键词
新能源电力系统
振荡薄弱点定位
频域
时域
希尔伯特-黄变换
new energy power system
weak point location for oscillation
frequency-domain
time-domain
Hilbert-Huang transform
