风电并网下储能参与电网一次调频控制策略*

doi:10.11985/2023.02.027

摘要/Abstract

摘要：

为进一步提高风电并网后电力系统运行的安全稳定性，提出一种针对风电波动性的新型储能参与电网调频控制策略。首先分析电力系统频率恢复不同阶段运行特性，并基于此提出储能参与电网调频的改进虚拟惯性响应和虚拟下垂控制，用于平抑风电并网的波动性；以储能电池剩余电量及负荷扰动量作为双输入，采用模糊控制策略，推导出虚拟下垂系数与双输入之间的平滑曲线关系；利用负荷扰动时的变化率进行负荷预测，预测超短下一时刻的负荷变化情况，计及风电波动功率，优化虚拟惯性控制和虚拟下垂控制的出力系数，以达到最优化调频效果，并提出三项评价指标对控制策略进行评价。最后以某区域电网模型为例，在试验台中进行仿真验证分析。仿真结果显示所提控制策略能够有效改善风电并网波动性带来的电网扰动，且对维持储能电池SOC(State of charge)具有积极意义。

关键词: 风电波动, 负荷预测, 模糊控制, 出力系数

Abstract:

In order to further improve the security and stability of power system operation after wind power grid connected, a new strategy of energy storage participating in power grid frequency modulation control is proposed. Firstly, the operation characteristics of power system in different stages of frequency recovery are analyzed. Based on this, the improved virtual inertia response and virtual droop control of energy storage participating in power grid frequency regulation are proposed to stabilize the fluctuation of wind power grid connection. Taking the remaining energy of energy storage battery and load disturbance as double input, the smooth curve relationship between virtual droop coefficient and double input is derived by using fuzzy control strategy. Using the change rate of load disturbance to predict the load change in the next ultra short time, considering the fluctuation power of wind power, the output coefficient of virtual inertia control and virtual droop control is optimized to achieve the optimal frequency modulation effect. Three evaluation indexes are proposed to evaluate the control strategy. Finally, taking a regional power grid model as an example, the simulation verification analysis is carried out in the test bench. The simulation results show that the proposed control strategy can effectively improve the grid disturbance caused by the fluctuation of wind power integration, and has positive significance for maintaining the state of charge(SOC) of energy storage battery.

Key words: Wind power fluctuation, load forecasting, fuzzy control, output coefficient

中图分类号:

TM712

宋兴荣, 熊尚峰, 王德顺, 李理, 胡安平, 陶以彬. 风电并网下储能参与电网一次调频控制策略^*[J]. 电气工程学报, 2023, 18(2): 260-268.

SONG Xingrong, XIONG Shangfeng, WANG Deshun, LI Li, HU Anping, TAO Yibin. Control Strategy of Energy Storage Participating in Primary Frequency Regulation with Wind Power Integration[J]. Journal of Electrical Engineering, 2023, 18(2): 260-268.

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参考文献 20

[1]	李建林, 马会萌, 惠东. 储能技术融合分布式可再生能源的现状及发展趋势[J]. 电工技术学报, 2016, 31(14):1-10.
	LI Jianlin, MA Huimeng, HUI Dong. Current situation and development trend of energy storage technology integrating distributed renewable energy[J]. Transactions of China Electrotechnical Society, 2016, 31(14):1-10.
[2]	戴兴建, 邓占峰, 刘刚. 大容量先进飞轮储能电源技术发展状况[J]. 电工技术学报, 2011, 26(7):133-140.
	DAI Xingjian, DENG Zhanfeng, LIU Gang. Development status of large capacity advanced flywheel energy storage power supply[J]. Transactions of China Electrotechnical Society, 2011, 26(7):133-140.
[3]	沈冠治, 李探, 徐冰亮. 考虑风电并网系统的储能优化配置[J]. 东北电力大学学报, 2018, 38(4):27-34.
	SHEN Guanzhi, LI Tan, XU Bingliang. Considering the optimal allocation of energy storage for wind power grid connected system[J]. Journal of Northeast Dianli University, 2018, 38(4):27-34.
[4]	张虹, 孙权, 李占军. 风氢耦合系统协同控制发电策略研究[J]. 东北电力大学学报, 2018, 38(3):15-23.
	ZHANG Hong, SUN Quan, LI Zhanjun. Research on power generation strategy of wind-hydrogen coupling system[J]. Journal of Northeast Dianli University, 2018, 38(3):15-23.
[5]	秦晓辉, 苏丽宁, 迟永宁. 大电网中虚拟同步发电机惯量支撑功率与一次调频功能定位辨析[J]. 电力系统自动化, 2018, 42(9):36-40.
	QIN Xiaohui, SU Lining, CHI Yongning. Analysis of inertia support power and primary frequency modulation function of virtual synchronous generator in large power grid[J]. Automation of Electric Power Systems, 2018, 42(9):36-40.
[6]	李欣然, 崔曦文, 黄际元. 电池储能电源参与电网一次调频的自适应控制策略[J]. 电工技术学报, 2019, 34(18):3897-3908.
	LI Xinran, CUI Xiwen, HUANG Jiyuan. Adaptive control strategy of battery energy storage power participating in primary frequency modulation of power grid[J]. Transactions of China Electrotechnical Society, 2019, 34(18):3897-3908.
[7]	崔红芬, 杨波, 蒋叶. 基于模糊控制和SOC自恢复储能参与二次调频控制策略[J]. 电力系统保护与控制, 2019, 47(22):1-10.
	CUI Hongfen, YANG Bo, JIANG Ye. Based on fuzzy control and SOC self-recovery energy storage participating in secondary frequency modulation control strategy[J]. Power System Protection and Control, 2019, 47(22):1-10.
[8]	李欣然, 邓涛, 黄际元. 储能电池参与电网调频的自适应控制策略[J]. 高电压技术, 2017, 43(7):2362-2369.
	LI Xinran, DENG Tao, HUANG Jiyuan. Adaptive control strategy for energy storage battery participating in power grid frequency modulation[J]. High Voltage Engineering, 2017, 43(7):2362-2369.
[9]	邓霞, 孙威, 肖海伟. 储能电池参与一次调频的综合控制方法[J]. 高电压技术, 2018, 44(4):1157-1165.
	DENG Xia, SUN Wei, XIAO Haiwei. Integrated control method of energy storage battery participating in primary frequency modulation[J]. High Voltage Engineering, 2018, 44(4):1157-1165.
[10]	羊博. 考虑负荷预测的储能参与电网调频控制策略研究[D]. 长沙: 湖南大学, 2018.
	YANG Bo. Research on frequency modulation control strategy for energy storage participation in power grid considering load prediction[D]. Changsha: Hunan University, 2018.
[11]	李妍, 荆盼盼, 王丽. 通用储能系统数学模型及其PSASP建模研究[J]. 电网技术, 2012, 36(1):51-57.
	LI Yan, JING Panpan, WANG Li. Research on mathematical model and PSASP modeling of General energy storage system[J]. Power System Technology, 2012, 36(1):51-57.
[12]	陈斌. 双馈风电机组参与电力系统频率调节的综合控制方法研究[D]. 成都: 西南交通大学, 2018.
	CHEN Bin. Research on integrated control method of doubly-fed wind turbine participating in frequency regulation of power system[D]. Chengdu: Southwest Jiaotong University, 2018.
[13]	黎淑娟, 李欣然, 黄际元. 考虑倍频特性的调频用储能电池优化配置[J]. 太阳能学报, 2020, 44(3):127-132.
	LI Shujuan, LI Xinran, HUANG Jiyuan. Optimal configuration of energy storage battery for frequency modulation considering frequency doubling characteristic[J]. Acta Energiae Solaris Sinica, 2020, 44(3):127-132.
[14]	方红艳, 马平. 考虑混合储能调频死区的自适应下垂控制策略[J]. 电气工程学报, 2021, 16(4):213-222.
	FANG Hongyan, MA Ping. Adaptive droop control strategy considering hybrid energy storage frequency modulation dead zone[J]. Journal of Electrical Engineering, 2021, 16(4):213-222.
[15]	黄际元, 李欣然, 曹一家. 面向电网调频应用的电池储能电源仿真模型[J]. 电力系统自动化, 2015, 35(18):20-24.
	HUANG Jiyuan, LI Xinran, CAO Yijia. Simulation model of battery energy storage power for power network frequency modulation application[J]. Automation of Electric Power Systems, 2015, 35(18):20-24.
[16]	汤杰, 李欣然, 黄际元. 以净效益最大为目标的储能电池参与二次调频的容量配置方法[J]. 电工技术学报, 2019, 34(5):963-972.
	TANG Jie, LI Xinran, HUANG Jiyuan. A capacity allocation method for secondary frequency modulation involving energy storage batteries with the goal of maximizing net benefit[J]. Transactions of China Electrotechnical Society, 2019, 34(5):963-972.
[17]	李军徽, 高卓, 应鸿. 基于动态下垂系数与SOC基点的储能一次调频控制策略[J]. 电力系统保护与控制, 2019, 41(14):1-11.
	LI Junhui, GAO Zhuo, YING Hong. Energy storage primary frequency modulation control strategy based on dynamic droop coefficient and SOC base point[J]. Power System Protection and Control, 2019, 41(14):1-11.
[18]	李亚男, 王倩, 宋文峰. 混介储能系统平滑风电出力的变分模态分解一模糊控制策略[J]. 电力系统保护与控制, 2019, 47(7):58-65.
	LI Yanan, WANG Qian, SONG Wenfeng. Variational modal decomposition and fuzzy control strategy for smooth wind power output of hybrid energy storage system[J]. Power System Protection and Control, 2019, 47(7):58-65.
[19]	邓睿. 电池储能技术在电力系统调频中的应用研究[D]. 武汉: 华中科技大学, 2017.
	Deng Rui. Research on the application of battery energy storage technology in power system frequency modulation[D]. Wuhan: Huazhong University of Science and Technology, 2017.
[20]	颜湘武, 崔森, 常文斐. 考虑储能自适应调节的双馈感应发电机一次调频控制策略[J]. 电工技术学报, 2021, 36(5):1027-1039.
	YAN Xiangwu, CUI Sen, CHANG Wenfei. Primary frequency modulation control strategy of doubly fed induction generator considering adaptive regulation of energy storage[J]. Transactions of China Electrotechnical Society, 2021, 36(5):1027-1039.

SOC	ΔP
SOC	NB	NS	ZO	PS	PB
NB	NB	NB	NS	ZO	ZO
NS	NB	NS	ZO	PS	PS
ZO	NS	NS	ZO	PS	PS
PS	ZO	ZO	ZO	PS	PB
PB	ZO	ZO	PS	PB	PB

参数	数值
等效惯性时间常数H_S/s	8
等效阻尼系数D_s	1
机械功率增益系数K_m	0.95
等效高压缸的工作比例F_H	0.3
等效载荷时间常数T_R/s	8
调速器调节系数R	0.05

策略	最大频率偏差/Hz
无储能	0.241
定K法	0.175
变K法	0.162
一般自适应法	0.192
本文策略	0.153