Control strategy of virtual synchronous generators based on adaptive control parameter setting

doi:10.3969/j.issn.2097-0706.2024.03.005

Abstract

Abstract:

The new power system with new energy as the main body presents the characteristics of "low inertia and low damping". Since the virtual synchronous generator （VSG） control strategy can simulate the mechanical motion equation and electromagnetic characteristics of the synchronous generator， the strategy can enhance the stability of the power system by making the distributed inverters possess the inertia and damping characteristics of the synchronous generator. However， the strategy will compromise their dynamic regulation performances. Thus， a VSG control strategy based on adaptive control parameter setting is proposed. Firstly，the effects of inertia moment and damping coefficient on system frequency and output in transient process are analyzed by establishing a small signal model of VSGs. Then，the correlation between the adaptive moment of inertia， angular velocity variation ratio and angular velocity offset，and the correlation between the adaptive damping coefficient and the angular velocity offset are analyzed by the power angle-frequency oscillation curve of a synchronous generator. The selection principle for the inertia moment and damping coefficient in different intervals is obtained，and their calculation formula and the trigger thresholds are designed. Furthermore，by adding adaptive droop coefficient considering the upper and lower limits of frequency modulation power，a control strategy of VSGs based on adaptive control parameter setting is proposed. Finally， the simulation analysis on the off-grid VSG model is built by Matlab/Simulink，and the simulation results verify that the proposed control strategy can reduce the frequency offset， and improve the frequency stability and dynamic regulation ability of the system.

Key words: new power system, virtual synchronous generator, moment of inertia, damping coefficient, adaptive control, droop coefficient

CLC Number:

TK01

DING Leyan, KE Song, YANG Jun, SHI Xingye. Control strategy of virtual synchronous generators based on adaptive control parameter setting[J]. Integrated Intelligent Energy, 2024, 46(3): 35-44.

Figures/Tables 21

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Table 1

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Table 2

Selected principle of inertia moment and damping coefficient in different intervals

区间	$d ω / d t$	$Δ ω$	$(d ω / d t) ⋅ Δ ω$	J	D
1	>0	>0	>0	增加	$Δ ω$ 较大时增加
2	<0	>0	<0	减小	$Δ ω$ 较大时增加
3	<0	<0	>0	增加	$Δ ω$ 较大时增加
4	>0	<0	<0	减小	$Δ ω$ 较大时增加

Table 2

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Table 3

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References 24

[1]	周孝信, 陈树勇, 鲁宗相, 等. 能源转型中我国新一代电力系统的技术特征[J]. 中国电机工程学报, 2018, 38(7): 1893-1904.
	ZHOU Xiaoxin, CHEN Shuyong, LU Zongxiang, et al. Technical characteristics of our new generation power system in energy transition[J]. Proceedings of the CSEE, 2018, 38(7): 1893-1904.
[2]	陈文哲, 孙海顺, 徐瑞林, 等. 电动汽车参与调频服务的云边融合分层调控技术研究[J]. 中国电机工程学报, 2023, 43(3): 914-925.
	CHEN Wenzhe, SUN Haishun, XU Ruilin, et al. Electric vehicles involved in FM service cloud edge fusion hierarchical control technology research[J]. Proceedings of the CSEE, 2023, 43(3): 914-925.
[3]	张剑云, 李明节. 新能源高渗透的电力系统频率特性分析[J]. 中国电机工程学报, 2020, 40(11): 3498-3507.
	ZHANG Jianyun, LI Mingjie. New energy power system frequency characteristic analysis of high permeability[J]. Proceedings of the CSEE, 2020, 40(11): 3498-3507.
[4]	吕志鹏, 盛万兴, 刘海涛, 等. 虚拟同步机技术在电力系统中的应用与挑战[J]. 中国电机工程学报, 2017, 37(2): 349-359.
	LV Zhipeng, SHENG Wanxing, LIU Haitao, et al. Virtual synchronous machine technology application in power system and challenges[J]. Proceedings of the CSEE, 2017, 37(2): 349-359.
[5]	DU Y, GUERRERO J M, CHANG L C, et al. Modeling, analysis, and design of a frequency-droop-based virtual synchronous generator for microgrid applications[C]// ECCE Asia Downunder(ECCE Asia),Melbourne,Australia, 2013: 643-649.
[6]	吕志鹏, 盛万兴, 钟庆昌, 等. 虚拟同步发电机及其在微电网中的应用[J]. 中国电机工程学报, 2014, 34(16): 2591-2603.
	LV Zhipeng, SHENG Wanxing, ZHONG Qingchang, et al. Virtual synchronous generator and its application in micro grid[J]. Proceedings of the CSEE, 2014, 34(16): 2591-2603.
[7]	LIU J, MIURA Y S, ISE T. Comparison of dynamic characteristics between virtual synchronous generator and droop control in inverter-based distributed generators[J]. IEEE Transactions on Power Electronics, 2015, 31(5): 3600-3611. doi: 10.1109/TPEL.2015.2465852
[8]	吴恒, 阮新波, 杨东升, 等. 虚拟同步发电机功率环的建模与参数设计[J]. 中国电机工程学报, 2015, 35(24): 6508-6518.
	WU Heng, RUAN Xinbo, YANG Dongsheng, et al. The modeling of virtual synchronous generator power ring and parameter design[J]. Proceedings of the CSEE, 2015, 35(24): 6508-6518.
[9]	WU H, RUAN X B, YANG D S. Small-signal modeling and parameters design for virtual synchronous generators[J]. IEEE Transactions on Industrial Electronics, 2016, 63(7): 4292-4303. doi: 10.1109/TIE.41
[10]	项雷军, 陈昊, 郭新华, 等. 基于模糊分数阶PID的含电动汽车的多能源微电网二次频率控制[J]. 电力自动化设备, 2021, 41(11): 74-80.
	XIANG Leijun, CHEN Hao, GUO Xinhua, et al. Based on fuzzy fractional order PID containing electric cars more secondary energy micro power grid frequency control[J]. Automation of Electrical Power Systems, 2021, 41(11): 74-80.
[11]	苏粟, 李家浩, 李泽宁, 等. 考虑用户需求的电动汽车虚拟同步机辅助调频控制策略[J]. 电力自动化设备, 2021, 41(11): 40-47.
	SU Li, LI Jiahao, LI Zening, et al. Considering the user requirements of electric vehicle virtual synchronous machine auxiliary frequency modulation control strategy[J]. Automation of Electrical Power Systems, 2021, 41(11): 40-47.
[12]	胡超, 张兴, 石荣亮, 等. 独立微电网中基于自适应权重系数的VSG协调控制策略[J]. 中国电机工程学报, 2017, 37(2): 516-524.
	HU Chao, ZHANG Xing, SHI Rongliang, et al. Independent micro power grid VSG coordinated control strategy based on adaptive weight coefficient[J]. Proceedings of the CSEE, 2017, 37(2): 516-524.
[13]	郭建祎, 樊友平. 基于改进粒子群算法的参数自适应控制策略[J]. 电机与控制学报, 2022, 26(6): 72-81.
	GUO Jianyi, FAN Youping. Based on improved particle swarm algorithm of parameter adaptive control strategy[J]. Electric Machines and Control, 2022, 26(6): 72-81.
[14]	李德胜, 李国策, 刘博. 基于虚拟同步发电机控制技术的V2G系统研究[J]. 电力系统保护与控制, 2021, 49(7): 127-133.
	LI Desheng, LI Guoce, LIU Bo. V2G system based on virtual synchronous generator control technology research[J]. Power System Protection and Control, 2021, 49(7): 127-133.
[15]	程子霞, 于洋, 柴旭峥. 基于协同自适应控制的光储VSG运行控制研究[J]. 电力系统保护与控制, 2020, 48(24): 79-85.
	CHENG Zixia, YU Yang, CHAI Xuzheng. Based on collaborative adaptive control of optical storage VSG run control research[J]. Power System Protection and Control, 2020, 48(24): 79-85.
[16]	BECK H P, HESSE R. Virtual synchronous machine[C]// Proceedings of 9th International Conference on Electrical Power Quality and Utilisation. Barcelona, Spain, 2007: 1-6.
[17]	ZHONG Q C, WEISS G. Synchronverters:Inverters that mimic synchronous generators[J]. IEEE Transactions on Industrial Electronics, 2011, 58(4): 1259-1267. doi: 10.1109/TIE.2010.2048839
[18]	ASHABANI M, MOHAMED Y A I. Novel comprehensive control framework for incorporating VSCs to smart power grids using bidirectional synchronous-VSC[J]. IEEE Transactions on Power Systems, 2014, 29(2): 943-957. doi: 10.1109/TPWRS.2013.2287291
[19]	DÍAZ N L, COELHO E A, VASQUEZ J C, et al. Stability analysis for isolated AC microgrids based on PV-active generators[C]// IEEE Energy Conversion Congress and Exposition (ECCE). Montrea, Canada, 2015: 4214-4221.
[20]	SHI K, CHEN C, SUN Y X, et al. Rotor inertia adaptive control and intertia matching strategy based on parallel virtual synchronous generators system[J]. IET Generation, Transmission and Distribution, 2020, 14(10):1854-1861. doi: 10.1049/gtd2.v14.10
[21]	YAO F J, ZHAO J B, LI X J, et al. RBF Neural network based virtual synchronous generator control with improved frequency stability[J]. IEEE Transactions on Industrial Informatics, 2021, 17(6): 4014-4024. doi: 10.1109/TII.9424
[22]	崔元捷, 张红兵, 何恒, 等. 微藻处理型废水及其特性研究进展[J]. 华电技术, 2021, 43(12): 10-16.
	CUI Yuanjie, ZHANG Hongbing, HE Heng, et al. Research progress of wastewater processed by microalgae[J]. Huadian Technology, 2021, 43(12): 10-16.
[23]	李新, 程凯杰, 朱良宽. 网络攻击下基于Round-Robin协议的数字化电力网络的递推状态估计[J]. 综合智慧能源, 2022, 44(12): 1-10. doi: 10.3969/j.issn.2097-0706.2022.12.001
	LI Xin, CHENG Kaijie, ZHU Liangkuan. Recursive state estimation for digitalized power grids subject to cyber attacks under Round-Robin protocol[J]. Integrated Intelligent Energy, 2022, 44(12): 1-10. doi: 10.3969/j.issn.2097-0706.2022.12.001
[24]	葛磊蛟, 崔庆雪, 李明玮, 等. 面向低碳经济运行的新型电力系统态势感知技术综述[J]. 综合智慧能源, 2023, 45(1): 1-13. doi: 10.3969/j.issn.2097-0706.2023.01.001
	GE Leijiao, CUI Qingxue, LI Mingwei, et al. Review on situational awareness technology in a low-carbon oriented new power system[J]. Integrated Intelligent Energy, 2023, 45(1): 1-13. doi: 10.3969/j.issn.2097-0706.2023.01.001

项目	ω_n	ξ	σ	t_s	结论
D恒定 J越大	越小	越小	越大	越长	J决定输出有功功率响应的振荡频率
J恒定 D越大	—	越大	越小	越小	D决定输出有功功率响应的振荡衰减速率

参数	取值	参数	取值
L₁/mH	0.23	D₀/(N·m·s·rad^-1)	800
R₁/Ω	0.2	K_j₁	0.25
C/μF	1	K_j₂	0.05
L₂/mH	1.20	K_d	10 000
R₂/Ω	0.05	c₁	0.8
U_dc/V	800	c₂	1.2
U_n/N	220	T_j	4.00
J₀/(kg·m²)	0.8	T_d	0.03