直流配网多滤波器交互影响机理分析

doi:10.16183/j.cnki.jsjtu.2021.423

上海交通大学学报 ›› 2023, Vol. 57 ›› Issue (4): 393-402.doi: 10.16183/j.cnki.jsjtu.2021.423

所属专题：《上海交通大学学报》2023年“新型电力系统与综合能源”专题

• 新型电力系统与综合能源 • 上一篇下一篇

直流配网多滤波器交互影响机理分析

王昊¹, 黄文焘¹(), 邰能灵¹, 余墨多¹, 孙国亮²

1.上海交通大学电力传输与功率变换控制教育部重点实验室,上海 200240
2.中国卫星海上测控部,江苏江阴 214400

收稿日期:2021-10-22 修回日期:2021-12-22 接受日期:2022-01-06 出版日期:2023-04-28 发布日期:2023-05-05
通讯作者: 黄文焘,副教授;E-mail:hwt8989@sjtu.edu.cn.
作者简介:王昊(1996-),硕士生,从事交直流配电网电能质量研究.
基金资助:
国家自然科学基金(51807117);上海市教委科研创新重大项目(2019-01-07-00-02-E00044)

Interaction Mechanism for Multiple Active Power Filters in DC Distribution Networks

WANG Hao¹, HUANG Wentao¹(), TAI Nengling¹, YU Moduo¹, SUN Guoliang²

1. Key Laboratory of Control of Power Transmission and Conversion of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China
2. China Satellite Marine Monitoring and Control Department, Jiangyin 214400, Jiangsu, China

Received:2021-10-22 Revised:2021-12-22 Accepted:2022-01-06 Online:2023-04-28 Published:2023-05-05

摘要/Abstract

摘要：

直流配网是配电系统的主要发展方向,受非线性设备、不平衡负载等因素影响,系统中极易产生二次谐波,严重威胁系统运行稳定性与用电设备安全性.在系统规模较大的直流配网中,多有源滤波器协同滤波是治理二次谐波的方法之一,但由于滤波器之间存在耦合干扰,滤波性能与效果差别较大.建立多滤波器诺顿等效并网模型,基于相对增益矩阵理论提出了多滤波器交互影响机理分析方法,构建了滤波器输出电流变化量与谐波源电流变化量矩阵关系,分析了直流配网线路参数和滤波器控制参数对滤波效果的影响.利用PSCAD/EMTDC软件建立含多直流滤波器的直流配电网模型,在不同场景下验证滤波器交互影响分析的合理性;并利用RT-LAB软件搭建半实物仿真模型,进一步验证了方法的有效性.

关键词: 直流配电网, 二次谐波, 直流滤波器, 相对增益矩阵, 交互影响机理

Abstract:

DC distribution network is the main development direction of the power distribution system. Due to the influence of electronic equipment and other factors, the system is very easy to produce second harmonics, which seriously affects the stability of the system and the safety of electrical equipment. Multi-filter collaborative filtering in DC distribution network has become one of the methods to control the second harmonic. However, due to the coupling interference between the filters, the filtering effect is affected by multiple factors. This paper establishes a Norton equivalent grid-connected model of multiple filters and proposes a method for analyzing the interaction mechanism of multiple filters based on the relative gain matrix theory. This method establishes the matrix relationship between the change in the output current of the filter and the change in the harmonic source current and analyzes the influence of the grid parameters and controller parameters in the multi-filter grid-connected system on the filtering effect of the filter, and proposes a reasonable parameter selection method. Finally, this paper establishes a DC distribution network model with multiple DC filters in PSCAD/EMTDC, and simulates the parameters affecting the filtering effect and verifies the rationality of the analysis in the scenario of multiple harmonic sources. In addition, it builds a semi-physical simulation model in RT-LAB to further verify the effectiveness of the method.

Key words: DC distribution network, second harmonic, DC active filter, relative gain matrix, interaction mechanism

中图分类号:

TM712

王昊, 黄文焘, 邰能灵, 余墨多, 孙国亮. 直流配网多滤波器交互影响机理分析[J]. 上海交通大学学报, 2023, 57(4): 393-402.

WANG Hao, HUANG Wentao, TAI Nengling, YU Moduo, SUN Guoliang. Interaction Mechanism for Multiple Active Power Filters in DC Distribution Networks[J]. Journal of Shanghai Jiao Tong University, 2023, 57(4): 393-402.

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参考文献 17

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参数	参数变化趋势	λ_c变化趋势
Z₁	增大	逐渐减小至1
K_p	增大	从λ_c>1逐渐减小至λ_c<1
k_pu	增大	不变
k_iu	增大	不变

参数	参数变化趋势	λ_c幅值变化
K_p1	增大	从λ_c>1减少至λ_c<1
K_p2	增大	从λ_c>1减少至λ_c<1
R/Ω	增大	逐渐减少至1
X/Ω	增大	不变

设备名称	参数	取值
AC/DC1	u_dc/V	1 000
	开关频率f_s/kHz	10
	直流侧稳压电容C_ac/μF	2 200
AC/DC2	u_dc/V	1 000
	f_s/kHz	2
	C_ac/μF	2 200
负荷	直流电阻性负荷R_dc/Ω	30
	P/kW	10
交流系统	电压U/kV	0.6
光伏电源	输出功率P_out/kW	5
线路	R/(Ω·km^-1)	0.4
	X/(μH·km^-1)	500

设备	参数	取值
DC-APF1	L/mH	12.5
	C/μF	2 200
	u_c/V	1 300
DC-APF2	L/mH	10
DC-APF3	C/μF	2 200
	u_c/V	1 300

Z₁/Ω	η₁/%	η₂/%	η₃/%
0.4	2.15	1.50	2.71
0.8	1.36	1.00	1.69
1.5	0.78	0.57	1.06
2.0	0.59	0.48	0.78

直流配网多滤波器交互影响机理分析

Interaction Mechanism for Multiple Active Power Filters in DC Distribution Networks

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K_p1	η₁/%	η₂/%	η₃/%
1	5.33	3.58	6.43
5	1.76	1.10	2.06
8	3.82	2.26	4.36
12	4.83	3.42	6.17