考虑惯量安全需求的风电场控制参数优化方法

doi:10.16183/j.cnki.jsjtu.2023.380

摘要/Abstract

摘要：

高比例新能源电力系统惯量和调频资源匮乏,存在较为突出的频率稳定问题.针对该问题,将风电场潜在频率支撑能力纳入电网频率控制措施,提出一种考虑惯量安全需求的风电场控制参数优化方法.事故发生后,首先根据频率安全限值在线计算满足暂态频率稳定的系统惯量和调频需求,形成惯量安全约束.然后,对风电场在不同风况下的惯量和调频能力建模,以事故后对应风况下风电场虚拟惯量和频率下垂参数调整量最小为目标,建立风电场频率控制参数的动态优化模型;最后,解算频率控制参数,基于改进的IEEE RTS-79系统进行算例测试.结果表明:所提参数优化方法有效改善了风电场暂态频率响应过程,有助于提升高比例新能源电力系统频率稳定裕度.

关键词: 风电场, 频率稳定, 惯量安全需求, 虚拟惯量, 下垂参数

Abstract:

The inertia and frequency regulation resources in power systems with a high proportion of renewable energy are scarce, resulting in prominent problems of frequency stability. To address these problems, this paper incorporates the potential frequency support capability of wind farms into the frequency control measures of the power grid, and proposes an optimization method for wind farm control parameters that considers the security requirements of system inertia. After a credible disturbance, the system inertia security requirement that meets the frequency stability constraint is calculated based on the transient frequency index limit. Then, the primary frequency regulation capability that wind farms can provide under different wind conditions is modeled with the goal of minimizing the adjustment of wind farm virtual inertia and frequency droop parameters under disturbances, and a dynamic optimization model for wind farm frequency control parameters is established. Finally, the frequency control parameters are calculated and numerical tests are conducted on the modified IEEE RTS-79 system. The results show that the proposed parameter optimization method effectively improves the transient frequency response process of wind farms, which helps enhance the frequency stability margin of the system.

Key words: wind farm, frequency stability, inertia security requirement, virtual inertia, droop parameter

中图分类号:

TM712

李鸿鑫, 钟祖浩, 卢艺, 文云峰. 考虑惯量安全需求的风电场控制参数优化方法[J]. 上海交通大学学报, 2025, 59(3): 323-332.

LI Hongxin, ZHONG Zuhao, LU Yi, WEN Yunfeng. Optimization of Frequency Control Parameters of Wind Farms Considering Inertia Security Requirement[J]. Journal of Shanghai Jiao Tong University, 2025, 59(3): 323-332.

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风电场	中低风况		高风况		风电场	中低风况		高风况
风电场	H_vir	k_w	H_vir	k_w	风电场	H_vir	k_w	H_vir	k_w
W2	[1, 3.5]	[10, 40]	[2.5, 6]	[20, 70]	W15	[1, 3]	[10, 40]	[2, 4.5]	[25, 75]
W4	[1, 5]	[20, 50]	[3, 8.5]	[30, 80]	W19	[1, 3]	[10, 40]	[2, 4.5]	[25, 75]
W7	[1, 5]	[20, 50]	[3, 8.5]	[30, 80]	W24	[1, 5]	[20, 50]	[3, 8.5]	[35, 85]
W9	[1, 5]	[25, 55]	[3.5, 8]	[35, 85]	W27	[1, 5]	[20, 50]	[3, 8.5]	[30, 80]
W12	[1, 6]	[30, 60]	[5, 9]	[40, 90]	W29	[1, 5]	[20, 50]	[4, 7.5]	[35, 85]

参数	W2	W4	W7	W9	W12
H_vir	2.871	4.592	4.492	4.615	5.934
k_w	38.153	43.709	43.709	43.709	46.487
参数	W15	W19	W24	W27	W29
H_vir	2.323	2.323	4.592	4.592	4.592
k_w	38.153	38.153	43.709	43.709	43.709

场景	R_{oCoF_max}/ (Hz·s^-1)	f_m/ Hz	f_ss/Hz
风电不参与调频	0.65	49.19	49.65
风电参数优化前指标	0.56	49.56	49.74
风电参数优化后指标	0.43	49.72	49.81
安全限值	0.50	49.60	49.80

运行状态	极限扰动量/%	系统惯量安全需求/(MW·s)
原始系统	-5.7	14623.62
中低风况	-8.1	23265.20
高风况	-9.2	29412.97