引用本文:巴文岚,文云峰,叶希,文明,黄明增,张武其.风电高渗透电网等效惯量概率预测方法[J].电力自动化设备,2023,43(3):
BA Wenlan,WEN Yunfeng,YE Xi,WEN Ming,HUANG Mingzeng,ZHANG Wuqi.Probability prediction method of equivalent inertia for high wind power penetration grid[J].Electric Power Automation Equipment,2023,43(3):
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风电高渗透电网等效惯量概率预测方法
巴文岚1, 文云峰1, 叶希2, 文明3, 黄明增1, 张武其1
1.湖南大学 电气与信息工程学院,湖南 长沙 410082;2.国网四川省电力公司,四川 成都 610041;3.国网湖南省电力有限公司经济技术研究院,湖南 长沙 410118
摘要:
在虚拟惯量控制技术的驱动下,风电高渗透电网包含不同形式惯量资源,系统等效惯量呈现复杂的非线性时变波动特征。为更好地诠释系统等效惯量的不确定性,提出了一种考虑风机虚拟惯量的系统等效惯量概率预测方法。首先利用数据驱动方法构建系统等效惯量的点预测模型,预判等效惯量的变化趋势;然后采用非参数核密度估计建立各时段预测误差概率密度函数,得到一定置信水平下待预测时刻系统等效惯量可能发生波动的区间范围。基于改进的IEEE RTS-79系统进行算例分析,结果表明所提方法与传统参数估计方法相比可靠性更高,能够为新型电力系统在低惯量场景下运行方式安排提供有益的辅助决策信息。
关键词:  双馈感应风机  系统等效惯量  惯量评估  惯量预测  不确定性
DOI:10.16081/j.epae.202209020
分类号:TM614
基金项目:国家自然科学基金资助项目(52077066)
Probability prediction method of equivalent inertia for high wind power penetration grid
BA Wenlan1, WEN Yunfeng1, YE Xi2, WEN Ming3, HUANG Mingzeng1, ZHANG Wuqi1
1.College of Electrical and Information Engineering, Hunan University, Changsha 410082, China;2.State Grid Sichuan Electric Power Company, Chengdu 610041, China;3.Economic & Technology Research Institute of State Grid Hunan Electric Power Co.,Ltd.,Changsha 410118, China
Abstract:
Driven by virtual inertia control technology, high wind power penetration grid contains different forms of inertia resources, and the system equivalent inertia presents the characteristic of complex nonlinear, time-varying and fluctuation. In order to better explain the uncertainty of system equivalent inertia, a probability prediction method of the system equivalent inertia considering the virtual inertia of wind turbine is proposed. Firstly, the point prediction model of system equivalent inertia is established through data-driven method, and the change trend of the equivalent inertia is predicted. Then, the non-parameter kernel density estimation is used to establish the probability density function of the prediction error for each time period, and the interval in which the system equivalent inertia may fluctuate under a certain confidence level at the prediction moment is obtained. An example is analyzed based on the modified IEEE RTS-79 system, and the results show that the proposed method is more reliable than the traditional parameter estimation method, it can provide useful decision-making information for new power system operation mode arrangement under low inertia scenarios.
Key words:  doubly-fed induction generator  system equivalent inertia  inertia estimation  inertia forecasting  uncertainty

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