Hybrid Energy Storage Participation in Secondary Frequency Regulation Control Strategy Based on Hierarchical Adaptive Control

doi:10.12096/j.2096-4528.pgt.260109

Abstract

Abstract:

Objectives When assisting the frequency regulation of the thermal power units, battery energy storage faces difficulties in coping with high-amplitude and high-frequency disturbances. To address these issues, a hybrid energy storage strategy for participation in secondary frequency regulation control, based on hierarchical adaptive control, is proposed. Methods The outer layer discusses the relationship between system residual energy and the proportional factor, proposing an adaptive proportional factor control strategy based on mathematical function methods. This strategy reasonably allocates regional control signals based on the system’s current frequency regulation capacity. Meanwhile, the inner layer optimizes the output control of the generation units and energy storage outputs. The unit output is controlled using a variable fuzzy PI controller, and energy storage output is controlled using a two-layer fuzzy control with variable time constant low-order filtering. This ensures that energy storage is not overcharged or over-discharged while adaptively allocating the frequency regulation signals. Simulation analysis is conducted using continuous load disturbances. Results Compared with the traditional fixed $K$ method, the proposed adaptive proportional factor control strategy reduces the maximum frequency deviation by 2.2%, reduces the energy storage contribution by 31.7%, and demonstrates better maintenance performance of state of charge. Conclusions The proposed control strategy can optimize the system’s frequency control and provide a new approach for maintaining grid frequency safety.

Key words: hybrid energy storage, thermal power unit, secondary frequency regulation, control strategy, adaptive proportional factor, state of charge, system residual energy

CLC Number:

TK 01

Ping ZHANG, Hongliang DI, Long HU, Yangang XUE, Haitao LIU. Hybrid Energy Storage Participation in Secondary Frequency Regulation Control Strategy Based on Hierarchical Adaptive Control[J]. Power Generation Technology, 2026, 47(1): 99-110.

Figures/Tables 22

Fig. 1 Secondary frequency regulation model for regional interconnected systems

Fig. 2 Proportional factor curves of thermal power unit output

Fig. 3 Proportional factor curves of SOC feedback of hybrid energy storage

Fig. 4 Comprehensive design process of adaptive control

Fig. 5 Schematic diagram of variable fuzzy principle

Fig. 6 Variable fuzzy PI structure

Tab. 1 Fuzzy rules of proportional parameter ΔKp

e_c	e
e_c	NB	NM	NS	ZO	PS	PM	PB
NB	PB	PB	PM	PM	PS	PS	ZO
NM	PB	PB	PM	PS	PS	ZO	NS
NS	PM	PM	PM	PS	ZO	NS	NS
ZO	PM	PM	PS	ZO	NS	NM	NM
PS	PS	PS	ZO	NS	NS	NM	NM
PM	PS	PS	NS	NM	NM	NM	NB
PB	ZO	NS	NM	NM	NM	NB	MN

Tab. 2 Fuzzy rules of integral parameter ΔKi

e_c	e
e_c	NB	NM	NS	ZO	PS	PM	PB
NB	NB	NB	NB	NM	NS	NS	ZO
NM	NB	NB	NM	NS	NS	ZO	PS
NS	NB	NM	NM	NS	ZO	PS	PS
ZO	NM	NM	NS	ZO	PS	PM	PM
PS	NM	NS	ZO	PS	PS	PM	PM
PM	NS	ZO	PS	PS	PM	PB	PB
PB	ZO	PS	PS	PM	PM	PB	PB

Fig. 7 Structure of variable time constant low-order filtering control

Tab. 3 Fuzzy rules of variable time constant Ti

$S o c, F$	$Δ P F$
$S o c, F$	NB	NS	ZO	PS	PB
NB	NB	NS	ZO	PS	PB
NS	NB	NS	ZO	PS	PB
ZO	ZO	ZO	ZO	ZO	ZO
PS	PB	PS	ZO	NS	NB
PB	PB	PS	ZO	NS	NB

Tab. 3 Fuzzy rules of variable time constant Ti

$S o c, F$	$Δ P F$
$S o c, F$	NB	NS	ZO	PS	PB
NB	NB	NS	ZO	PS	PB
NS	NB	NS	ZO	PS	PB
ZO	ZO	ZO	ZO	ZO	ZO
PS	PB	PS	ZO	NS	NB
PB	PB	PS	ZO	NS	NB

Fig. 8 Control structure of energy storage unit

Tab. 4 Fuzzy rules for optimizing signal Ace,SF

$A c e, F$	$S o c, F$
$A c e, F$	NB	NM	NS	ZO	PS	PM	PB
NB	ZO	ZO	NM	NB	NB	NB	NB
NM	ZO	NS	NS	NM	NM	NM	NM
NS	ZO	NS	NS	NS	NS	NS	NS
ZO	ZO	ZO	ZO	ZO	ZO	ZO	ZO
PS	PS	PS	PS	PS	PS	PS	ZO
PM	PM	PM	PM	PM	PS	PS	ZO
PB	PB	PB	PM	PB	PM	PS	ZO

Tab. 4 Fuzzy rules for optimizing signal Ace,SF

$A c e, F$	$S o c, F$
$A c e, F$	NB	NM	NS	ZO	PS	PM	PB
NB	ZO	ZO	NM	NB	NB	NB	NB
NM	ZO	NS	NS	NM	NM	NM	NM
NS	ZO	NS	NS	NS	NS	NS	NS
ZO	ZO	ZO	ZO	ZO	ZO	ZO	ZO
PS	PS	PS	PS	PS	PS	PS	ZO
PM	PM	PM	PM	PM	PS	PS	ZO
PB	PB	PB	PM	PB	PM	PS	ZO

Tab. 5 Fuzzy rules for optimizing signal Ace,SB

$A c e, B$	$S o c, B$
$A c e, B$	NB	NM	NS	ZO	PS	PM	PB
NB	ZO	ZO	NM	NM	NM	NM	NB
NM	ZO	NS	NS	NS	NM	NM	NM
NS	ZO	NS	NS	NS	NS	NS	NS
ZO	ZO	ZO	ZO	ZO	ZO	ZO	ZO
PS	PS	PS	PS	PS	PS	PS	ZO
PM	PM	PM	PM	PM	PS	PS	ZO
PB	PB	PM	PM	PM	PM	PS	ZO

Tab. 5 Fuzzy rules for optimizing signal Ace,SB

$A c e, B$	$S o c, B$
$A c e, B$	NB	NM	NS	ZO	PS	PM	PB
NB	ZO	ZO	NM	NM	NM	NM	NB
NM	ZO	NS	NS	NS	NM	NM	NM
NS	ZO	NS	NS	NS	NS	NS	NS
ZO	ZO	ZO	ZO	ZO	ZO	ZO	ZO
PS	PS	PS	PS	PS	PS	PS	ZO
PM	PM	PM	PM	PM	PS	PS	ZO
PB	PB	PM	PM	PM	PM	PS	ZO

Fig. 9 Framework of control strategy

Tab. 6 Simulation parameters

参数	区域1	区域2	参数	区域1	区域2
$M$	10	10	$T F$	0.01
$D$	1	1	$T B$	0.03
$T g$	0.08	0.06	$S o c,, l o w$	0.45
$T C H$	0.3	0.3	$S o c, h i g h$	0.55
$T R H$	10	10	$K P$		-0.822
$F H P$	0.5	0.5	$K I$		-0.16
$a$	20	20	$T t$	1.59	1.59
$b$	21	21

Tab. 6 Simulation parameters

参数	区域1	区域2	参数	区域1	区域2
$M$	10	10	$T F$	0.01
$D$	1	1	$T B$	0.03
$T g$	0.08	0.06	$S o c,, l o w$	0.45
$T C H$	0.3	0.3	$S o c, h i g h$	0.55
$T R H$	10	10	$K P$		-0.822
$F H P$	0.5	0.5	$K I$		-0.16
$a$	20	20	$T t$	1.59	1.59
$b$	21	21

Fig. 10 Continuous disturbance load curve

Fig. 11 Comparison of response curves of different strategies under continuous disturbance load curve

Tab. 7 Evaluation indicators of different strategies under continuous disturbance load

方案	$\| Δ f m \|$ /Hz	$Δ f r m s$ /Hz	$Q H E S S$ /pu	$S o c, r m s$ /pu
本文策略	0.004 4	0.001 6	-2.448 2	0.573 6
方案1	0.004 5	0.001 6	-3.583 1	0.570 1
方案2	0.004 5	0.001 6	-4.756 0	0.567 3

Tab. 7 Evaluation indicators of different strategies under continuous disturbance load

方案	$\| Δ f m \|$ /Hz	$Δ f r m s$ /Hz	$Q H E S S$ /pu	$S o c, r m s$ /pu
本文策略	0.004 4	0.001 6	-2.448 2	0.573 6
方案1	0.004 5	0.001 6	-3.583 1	0.570 1
方案2	0.004 5	0.001 6	-4.756 0	0.567 3

Fig. 12 Comparison of response curves of different controllers under continuous disturbance load curve

Tab. 8 Evaluation indicators of different controllers under continuous disturbance load

方案	$\| Δ f m \|$ /Hz	$Δ f r m s$ /Hz	$Q g$ /pu	$P g, r m s$ /pu
变模糊PI	0.004 4	0.001 6	7.608 9	0.018 5
PI	0.004 5	0.001 6	12.291 2	0.019 5

Tab. 8 Evaluation indicators of different controllers under continuous disturbance load

方案	$\| Δ f m \|$ /Hz	$Δ f r m s$ /Hz	$Q g$ /pu	$P g, r m s$ /pu
变模糊PI	0.004 4	0.001 6	7.608 9	0.018 5
PI	0.004 5	0.001 6	12.291 2	0.019 5

Fig. 13 Comparison of response curves of different control methods under continuous disturbance load curve

Tab. 9 Evaluation indicators of different control methods under continuous disturbance load

方案	$\| Δ f m \|$ /Hz	$Δ f r m s$ /Hz	$Q B$ /pu	$S o c B, r m s$ /pu	$Q F$ /pu	$S o c F, r m s$ /pu
本文策略	0.004 4	0.001 6	5.836 5	0.448 6	-3.489 9	0.706 4
方案1	0.004 4	0.001 6	6.115 9	0.454 8	-1.707 5	0.668 2
方案2	0.005 3	0.001 8	0.774 7	0.495 0	0.459 1	0.598 2

Tab. 9 Evaluation indicators of different control methods under continuous disturbance load

方案	$\| Δ f m \|$ /Hz	$Δ f r m s$ /Hz	$Q B$ /pu	$S o c B, r m s$ /pu	$Q F$ /pu	$S o c F, r m s$ /pu
本文策略	0.004 4	0.001 6	5.836 5	0.448 6	-3.489 9	0.706 4
方案1	0.004 4	0.001 6	6.115 9	0.454 8	-1.707 5	0.668 2
方案2	0.005 3	0.001 8	0.774 7	0.495 0	0.459 1	0.598 2

References 24

[1]	李国庆，刘先超，辛业春，等．含高比例新能源的电力系统频率稳定研究综述[J]．高电压技术，2024，50(3)：1165-1181．
	LI G Q， LIU X C， XIN Y C，et al ．Research on frequency stability of power system with high penetration renewable energy：a review[J]．High Voltage Engineering，2024，50(3)：1165-1181．
[2]	郝玲，陈磊，黄怡涵，等．新型电力系统下燃煤火电机组一次调频面临的挑战与展望[J]．电力系统自动化，2024，48(8)：14-29．
	HAO L， CHEN L， HUANG Y H，et al ．Challenges and prospects of primary frequency regulation of coal-fired thermal power units for new power system[J]．Automation of Electric Power Systems，2024，48(8)：14-29．
[3]	江守其，张海峰，付贵，等．提升光储并网系统频率稳定性的协调控制策略[J]．电力建设，2025，46(8)：138-149．
	JIANG S Q， ZHANG H F， FU G，et al ．Coordinated control strategies for enhancing frequency stability of photovoltaic and storage networking systems[J]．Electric Power Construction，2025，46(8)：138-149．
[4]	张俊，蒲天骄，高文忠，等．电力系统智能计算的关键技术及应用展望[J]．发电技术，2025，46(3)：421-437．
	ZHANG J， PU T J， GAO W Z，et al ．Key technologies and application prospects of intelligent computing in power systems[J]．Power Generation Technology，2025，46(3)：421-437．
[5]	徐鹏，郭新元，赵伟，等．功率与频率耦合下100%新能源电力系统的潮流分析模型[J]．智慧电力，2024，52(12)：73-79．
	XU P， GUO X Y， ZHAO W，et al ．Power flow analysis model of power system with 100% renewable energy under power-frequency coupling[J]．Smart Power，2024，52(12)：73-79．
[6]	沈赋，曹旸，徐潇源，等．高比例可再生能源电力系统惯量预测方法研究综述[J]．电力建设，2025，46(8)：116-128．
	SHEN F， CAO Y， XU X Y，et al ．A review of inertia prediction methods for power system with high penetration renewable energy sources[J]．Electric Power Construction，2025，46(8)：116-128．
[7]	刘海涛，朱康凯，王宇昊，等．考虑“源-荷”双侧调频的电力系统双层优化调度模型[J]．电测与仪表，2025，62(11)：154-166．
	LIU H T， ZHU K K， WANG Y H，et al ．Bi-level unit commitment optimized dispatching model of power system with ‘source-load’ bilateral frequency regulation[J]．Electrical Measurement & Instrumentation，2025，62(11)：154-166．
[8]	董武，张健，周勤勇，等．中国电力系统安全稳定性演化综述[J]．中国电力，2025，58(1)：115-127．
	DONG W， ZHANG J， ZHOU Q Y，et al ．An overview of the evolution of security and stability of China’s power system[J]．Electric Power，2025，58(1)：115-127．
[9]	何鑫，刘翠，李芸．不同运行方式的大规模新能源接入电网后的调频特性研究[J]．电力科学与技术学报，2024，39(3)：168-176．
	HE X， LIU C， LI Y ．Study on frequency regulation characteristics of power grids after large-scale new energy integration under different operation modes[J]．Journal of Electric Power Science and Technology，2024，39(3)：168-176．
[10]	梅勇，高永强，李成翔，等．计及新能源接入的孤网运行全过程动态仿真研究[J]．广东电力，2024，37(1)：68-75．
	MEI Y， GAO Y Q， LI C X，et al ．Dynamic simulation study of the whole process of isolated network operation considering new energy connection[J]．Guangdong Electric Power，2024，37(1)：68-75．
[11]	王士博，孔令国，蔡国伟，等．电力系统氢储能关键应用技术现状、挑战及展望[J]．中国电机工程学报，2023，43(17)：6660-6681．
	WANG S B， KONG L G， CAI G W，et al ．Current status，challenges and prospects of key application technologies for hydrogen storage in power system[J]．Proceedings of the CSEE，2023，43(17)：6660-6681．
[12]	王放放，杨鹏威，赵光金，等．新型电力系统下火电机组灵活性运行技术发展及挑战[J]．发电技术，2024，45(2)：189-198．
	WANG F F， YANG P W， ZHAO G J，et al ．Development and challenge of flexible operation technology of thermal power units under new power system[J]．Power Generation Technology，2024，45(2)：189-198．
[13]	杨水丽，李建林，李蓓，等．电池储能系统参与电网调频的优势分析[J]．电网与清洁能源，2013，29(2)：43-47．
	YANG S L， LI J L， LI B，et al ．Advantages of battery energy storage system for frequency regulation[J]．Power System and Clean Energy，2013，29(2)：43-47．
[14]	陈海生，李泓，马文涛，等．2021年中国储能技术研究进展[J]．储能科学与技术，2022，11(3)：1052-1076．
	CHEN H S， LI H， MA W T，et al ．Research progress of energy storage technology in China in 2021[J]．Energy Storage Science and Technology，2022，11(3)：1052-1076．
[15]	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 X， SUN W， XIAO H W ．Integrated control strategy of battery energy storage system in primary frequency regulation[J]．High Voltage Engineering，2018，44(4)：1157-1165．
[16]	SOFIA GUZMAN E N， ARRIAGA M， CAÑIZARES C A，et al ．Regulation signal design and fast frequency control with energy storage systems[J]．IEEE Transactions on Power Systems，37(1)：224-236． doi:10.1109/tpwrs.2021.3086075
[17]	吴启帆，宋新立，张静冉，等．电池储能参与电网一次调频的自适应综合控制策略研究[J]．电网技术，2020，44(10)：3829-3836．
	WU Q F， SONG X L， ZHANG J R，et al ．Study on self-adaptation comprehensive strategy of battery energy storage in primary frequency regulation of power grid[J]．Power System Technology，2020，44(10)：3829-3836．
[18]	PAN X， XU H， SONG J，et al ．Capacity optimization of battery energy storage systems for frequency regulation[C]//2015 IEEE International Conference on Automation Science and Engineering (CASE)．Gothenburg，Sweden：IEEE，2015：1139-1144． doi:10.1109/coase.2015.7294251
[19]	TAN Y， MUTTAQI K M， CIUFO P，et al ．Enhanced frequency regulation using multilevel energy storage in remote area power supply systems[J]．IEEE Transactions on Power Systems，2018，34(1)：163-170． doi:10.1109/tpwrs.2018.2867190
[20]	韩健民，薛飞宇，梁双印，等．模糊控制优化下的混合储能系统辅助燃煤机组调频仿真[J]．储能科学与技术，2022，11(7)：2188-2196．
	HAN J M， XUE F Y， LIANG S Y，et al ．Hybrid energy storage system assisted frequency modulation simulation of the coal-fired unit under fuzzy control optimization[J]．Energy Storage Science and Technology，2022，11(7)：2188-2196．
[21]	郭强，陈崇德，胡阳，等．飞轮和锂电池储能联合光伏发电一次调频控制[J]．电力系统及其自动化学报，2023，35(11)：1-9．
	GUO Q， CHEN C D， HU Y，et al ．Flywheel and lithium battery energy storage combined with photovoltaic power generation participating in primary frequency regulation control[J]．Proceedings of the CSU-EPSA，2023，35(11)：1-9．
[22]	孟德方，蔚伟，钱玉良．基于调频需求分配的混合储能调频双层控制策略[J]．陕西科技大学学报，2023，41(5)：161-168．
	MENG D F， WEI W， QIAN Y L ．Dual-layer control strategy for hybrid energy storage frequency regulation based on frequency regulation demand[J]．Journal of Shaanxi University of Science and Technology，2023，41(5)：161-168．
[23]	骆钊，高培淇，聂灵峰，等．风-铝联合系统协同频率控制策略研究[J]．电机与控制应用，2023，50(4)：49-57．
	LUO Z， GAO P Q， NIE L F，et al ．Research on cooperative frequency control strategy with wind-aluminum combination system[J]．Electric Machines & Control Application，2023，50(4)：49-57．
[24]	王椿，贾磊，王国辉，等．车辆磁流变半主动悬架变论域模糊PID控制[J]．现代制造工程，2023(8)：59-65．
	WANG C， JIA L， WANG G H，et al ．Variable universe fuzzy PID control for vehicle semi-active suspension with magnetorheological dampers[J]．Modern Manufacturing Engineering，2023(8)：59-65．