基于AHFS与RBF的光储VSG虚拟惯量灵活控制研究

doi:10.11930/j.issn.1004-9649.202410050

摘要/Abstract

摘要：

针对传统光储虚拟同步发电机（virtual synchronous generator，VSG）并网存在有功超调和系统动态振荡的问题，提出一种基于有功高频反馈抑制（active high-frequency feedback suppression，AHFS）与径向基函数（radial basis function，RBF）的光储VSG虚拟惯量灵活控制策略。引入一阶滤波环节，提高系统高频抑制能力，在功率反馈环节中加入有功微分项，改变系统的动态性能；构造考虑系统有功超调量和上升时间2项指标的目标函数，利用粒子群算法求解有功微分系数的最优值；结合RBF神经网络设计虚拟惯量自适应调节控制策略，根据系统角速度及其变化率实时在线灵活调整虚拟惯量。联合控制方法有效改善了传统VSG存在输出有功超调和频率过冲问题。结果表明，所提控制策略可有效抑制频率偏差和有功超调，提升了系统的暂态稳定性。

关键词: 光储VSG, 电网扰动, 频率偏差, 有功振荡, RBF神经网络

Abstract:

To address the issue of active power overshoot and the challenge of system dynamic oscillations in grid integration of traditional photovoltaic and energy storage virtual synchronous generators (VSGs), This article proposes a virtual inertia flexible control strategy for photovoltaic storage VSG based on active high-frequency feedback suppression (AHFS) and radial basis function (RBF). Firstly, a first-order filtering link is introduced to enhance the system's high-frequency suppression capability, and an active power differential term is added to the power feedback loop to modify the dynamic performance of the system. Secondly, an objective function considering both active power overshoot and rise time is constructed, and the optimal active power differential coefficient is determined via particle swarm optimization (PSO) algorithm. Finally, an adaptive control strategy for virtual inertia is designed using RBF neural network, which can flexibly adjust the virtual inertia in real-time based on the system's angular velocity and its rate of change. The coordinated control method effectively mitigates the issues of power overshoot and frequency overshooting in traditional VSGs. Simulation results show that the proposed control strategy can effectively suppress frequency deviation and active power overshoot, thereby enhancing the system's transient stability.

Key words: photovoltaic storage VSG, grid disturbance, frequency deviation, active power oscillation, RBF neural network

肖湘奇, 邓汉钧, 邹晟, 肖建红, 李恺, 马斌. 基于AHFS与RBF的光储VSG虚拟惯量灵活控制研究[J]. 中国电力, 2025, 58(9): 33-43.

XIAO Xiangqi, DENG Hanjun, ZOU Sheng, XIAO Jianhong, LI Kai, MA Bin. Virtual Inertia Flexible Control of Photovoltaic Storage VSG Based on AHFS and RBF[J]. Electric Power, 2025, 58(9): 33-43.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202410050

https://www.electricpower.com.cn/CN/Y2025/V58/I9/33

图/表 16

图 1 光储VSG电路拓扑

Fig.1 Schematic diagram of photovoltaic energy storage VSG circuit

图 2 VSG控制环

Fig.2 VSG control loop

图 3 传统VSG极点分布

Fig.3 Pole distribution diagram of traditional VSG

图 4 基于AHFS-VSG有功-频率控制环

Fig.4 AHFS-VSG-based active frequency control loop

图 5 AHFS-VSG的极点分布

Fig.5 Pole distribution diagram of AHFS-VSG

图 6 不同Kp值下有功输出的暂态响应对比

Fig.6 Comparison of active power output ransient response for different Kp values

图 7 同步发电机功角与角频率变化曲线

Fig.7 Synchronous generator power angle and angular frequency variation curves

表 1 不同动态过程下J选取规则

Table 1 Selection rules for J under different dynamic processes

$\Delta \omega $	${\text{d}}\omega /{\text{d}}t$	J
＞0	＞0	增大
＞0	＜0	减小
＜0	＜0	增大
＜0	＞0	减小

图 8 基于RBF的AHFS-VSG结构

Fig.8 AHFS-VSG structure based on RBF

图 9 RBF神经网络结构

Fig.9 RBF neural network structure

图 10 基于RBF的AHFS-VSG虚拟惯量灵活控制流程

Fig.10 Flexible control flow chart of RBF-based AHFS-VSG virtual inertia

图 11 半实物仿真实验平台

Fig.11 Semi-physical simulation experiment platform

表 2 仿真参数

Table 2 Simulation parameters

参数		数值
直流侧电压 V_dc/V		1000
额定有功功率 P_N/kW		100
额定角频率 ω₀/(rad·s^–1)		314
额定频率 f/Hz		50
滤波电感 L_f/mH		2
线路电感 X_g/mH		1.2
无功下垂控制系数 k_q		1000
有功下垂控制系数 k_p		1900
转动惯量 J/(kg.m²)		2
阻尼系数 D		0
开关频率 f_s/kHz		2.5

图 12 转动惯量J输出结果对比

Fig.12 Comparison of output results of moment of inertia J

图 13 有功扰动输出结果对比

Fig.13 Comparison of active disturbance output results

图 14 频率扰动输出结果对比

Fig.14 Comparison of frequency disturbance output results

参考文献 25

1	黄龑, 郝迎鹏, 汪慧娴, 等. 基于二阶统一模型的分布式发电并网同步控制研究[J]. 中国电力, 2023, 56 (12): 41- 50. DOI
	HUANG Yan, HAO Yingpeng, WANG Huixian, et al. Research on synchronization control of distributed generation based on second-order unified model[J]. Electric Power, 2023, 56 (12): 41- 50. DOI
2	吴磊, 韩冬, 毛贵江, 等. 适应分布式发电市场化交易的过网费计算方法[J]. 上海交通大学学报, 2023, 57 (7): 887- 898.
	WU Lei, HAN Dong, MAO Guijiang, et al. Calculation method of network usage charge for market-oriented trading in distributed generation market[J]. Journal of Shanghai Jiaotong University, 2023, 57 (7): 887- 898.
3	李小菊, 李青兰, 詹航, 等. 动态无功电压控制对频率振荡的影响及附加阻尼控制[J]. 南方电网技术, 2021, 15 (6): 71- 77.
	LI Xiaoju, LI Qinglan, ZHAN Hang, et al. Effect of dynamic reactive power-voltage control on frequency oscillation and supplementary damping control[J]. Southern Power System Technology, 2021, 15 (6): 71- 77.
4	詹长江, 吴恒, 王雄飞, 等. 构网型变流器稳定性研究综述[J]. 中国电机工程学报, 2023, 43 (6): 2339- 2359.
	ZHAN Changjiang, WU Heng, WANG Xiongfei, et al. An overview of stability studies of grid-forming voltage source converters[J]. Proceedings of the CSEE, 2023, 43 (6): 2339- 2359.
5	GUO L L, XU Z Y, JIN N, et al. A weighted voltage model predictive control method for a virtual synchronous generator with enhanced parameter robustness[J]. Protection and Control of Modern Power Systems, 2021, 6 (4): 1- 11.
6	张茜, 毛义鹏, 余乐, 等. 适用于无直流侧电压传感器单相级联H桥型光伏逆变器的直接功率模型预测控制方法[J]. 中国电力, 2022, 55 (2): 172- 180. DOI
	ZHANG Qian, MAO Yipeng, YU Le, et al. Direct power model predictive control method for DC-side sensor-less single-phase cascaded H-bridges photovoltaic inverters[J]. Electric Power, 2022, 55 (2): 172- 180. DOI
7	杜毅, 郑超, 孙华东. 构网型VSC暂态稳定机理及改进限幅策略[J]. 中国电机工程学报, 2024, 44 (10): 3753- 3766.
	DU Yi, ZHENG Chao, SUN Huadong. Transient stability mechanism analysis of the grid forming voltage source converter and the improved limiting method[J]. Proceedings of the CSEE, 2024, 44 (10): 3753- 3766.
8	张江丰, 柯松, 陈文进, 等. 光伏电站自备用可调的虚拟同步控制调频策略[J]. 中国电力, 2024, 57 (11): 108- 118. DOI
	ZHANG Jiangfeng, KE Song, CHEN Wenjin, et al. Virtual synchronous control frequency regulation strategy for adjustable self-standby rate in photovoltaic plants[J]. Electric Power, 2024, 57 (11): 108- 118. DOI
9	戎士洋, 范辉, 梁纪峰, 等. 多VSG单元的惯量协调控制策略研究[J]. 电力科学与技术学报, 2024, 39 (2): 170- 180.
	RONG Shiyang, FAN Hui, LIANG Jifeng, et al. Research on inertia coordinated control strategy of multiple VSG cells[J]. Journal of Electric Power Science and Technology, 2024, 39 (2): 170- 180.
10	王立娜, 王逸超, 谭丽平, 等. 基于自适应指数函数的变参数VSG控制[J]. 电力科学与技术学报, 2023, 38 (3): 124- 131.
	WANG Lina, WANG Yichao, TAN Liping, et al. Variable parameter VSG control based on adaptive exponential function[J]. Journal of Electric Power Science and Technology, 2023, 38 (3): 124- 131.
11	林磊, 温步瀛. 基于动态特性的改进型VSG电压控制策略[J]. 广东电力, 2020, 33 (11): 44- 50. DOI
	LIN Lei, WEN Buying. Improved voltage control strategy of VSG based on dynamic characteristics[J]. Guangdong Electric Power, 2020, 33 (11): 44- 50. DOI
12	杨旭红, 金宏艳, 刘众鑫, 等. 光储逆变器的虚拟同步机自适应控制策略研究[J]. 电力科学与技术学报, 2024, 39 (2): 181- 189.
	YANG Xuhong, JIN Hongyan, LIU Zhongxin, et al. Research on adaptive control strategy of virtual synchronous machine applied for the photovoltaic and energy storage inverter[J]. Journal of Electric Power Science and Technology, 2024, 39 (2): 181- 189.
13	杨力, 朱晓纲, 李勇, 等. 规模化储能虚拟同步控制策略及其惯量分析[J]. 电力科学与技术学报, 2024, 39 (2): 190- 197.
	YANG Li, ZHU Xiaogang, LI Yong, et al. Virtual synchronous control strategy and inertia analysis of large-scale energy storage[J]. Journal of Electric Power Science and Technology, 2024, 39 (2): 190- 197.
14	LI M X, YU P, HU W H, et al. Phase feedforward damping control method for virtual synchronous generators[J]. IEEE Transactions on Power Electronics, 2022, 37 (8): 9790- 9806. DOI
15	岳家辉, 张新燕, 周鹏, 等. 基于自适应惯量阻尼的双馈风电机组虚拟同步控制策略[J]. 电力系统及其自动化学报, 2021, 33 (9): 40- 48.
	YUE Jiahui, ZHANG Xinyan, ZHOU Peng, et al. Virtual synchronization control strategy for double-fed wind turbines based on adaptive inertia damping[J]. Proceedings of the CSU-EPSA, 2021, 33 (9): 40- 48.
16	于晶荣, 孙文, 于佳琪, 等. 基于惯性自适应的并网逆变器虚拟同步发电机控制[J]. 电力系统保护与控制, 2022, 50 (4): 137- 144.
	YU Jingrong, SUN Wen, YU Jiaqi, et al. Virtual synchronous generator control of a grid-connected inverter based on adaptive inertia[J]. Power System Protection and Control, 2022, 50 (4): 137- 144.
17	兰征, 龙阳, 曾进辉, 等. 考虑超调的虚拟同步发电机暂态功率振荡抑制策略[J]. 电力系统自动化, 2022, 46 (11): 131- 141.
	LAN Zheng, LONG Yang, ZENG Jinhui, et al. Transient power oscillation suppression strategy of virtual synchronous generator considering overshoot[J]. Automation of Electric Power Systems, 2022, 46 (11): 131- 141.
18	李新, 刘国梁, 杨苒晨, 等. 具有暂态阻尼特性的虚拟同步发电机控制策略及无缝切换方法[J]. 电网技术, 2018, 42 (7): 2081- 2088.
	LI Xin, LIU Guoliang, YANG Ranchen, et al. VSG control strategy with transient damping term and seamless switching control method[J]. Power System Technology, 2018, 42 (7): 2081- 2088.
19	KARIMI A, KHAYAT Y, NADERI M, et al. Inertia response improvement in AC microgrids: a fuzzy-based virtual synchronous generator control[J]. IEEE Transactions on Power Electronics, 2020, 35 (4): 4321- 4331. DOI
20	朱平平. 基于模糊PID的核环境机器人电液比例位置控制系统设计研究[D]. 衡阳: 南华大学, 2020.
	ZHU Pingping. Design and research of electro-hydralicproportional position control system fornuclear environment robot based on fuzzy PID. Hengyang: University of South China, 2020.
21	胡昆, 李思超, 鲁元昊, 等. 基于模糊 PID 的电液位置伺服系统建模与仿真[J]. 机电工程技术, 2023, 52 (4): 90- 94. DOI
	HU Kun, LI Sichao, LU Yuanhao, et al. Modeling and simulation of electro-hydraulic position servo system based on fuzzy PID[J]. Mechanical Electrical Enginering Technology, 2023, 52 (4): 90- 94. DOI
22	WANG Y, WAI R J. Adaptive fuzzy-neural-network power decoupling strategy for virtual synchronous generator in micro-grid[J]. IEEE Transactions on Power Electronics, 2022, 37 (4): 3878- 3891. DOI
23	赵金辉, 刘立晶, 杨学军, 等. 播种机开沟深度控制系统的设计与室内试验[J]. 农业工程学报, 2015, 31 (6): 35- 41.
	ZHAO Jinhui, LIU Lijing, YANG Xuejun, et al. Design and laboratory test of control system for depth of furrow opening[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31 (6): 35- 41.
24	JIN W G, CHEN L, CHEN H K, et al. A novel evaluation method of the hosting capacity of multiple renewable energy stations accessed into a power system[J]. Energy Reports, 2023, 9, 56- 65. DOI
25	张子星, 赵晋斌, 曾志伟, 等. 基于RBF的VSG虚拟惯量和动态阻尼补偿自适应控制[J]. 电力系统保护与控制, 2024, 52 (2): 155- 164.
	ZHANG Zixing, ZHAO Jinbin, ZENG Zhiwei, et al. VSG virtual inertia and dynamic damping compensation adaptive control based on RBF[J]. Power System Protection and Control, 2024, 52 (2): 155- 164.

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