基于分层自适应控制的混合储能参与二次调频控制策略

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

发电技术 ›› 2026, Vol. 47 ›› Issue (1): 99-110.DOI: 10.12096/j.2096-4528.pgt.260109

基于分层自适应控制的混合储能参与二次调频控制策略

张萍¹, 邸宏亮¹, 胡龙¹, 薛延刚², 刘海涛¹

^1.兰州理工大学电气工程与信息工程学院，甘肃省兰州市 733000
^2.重庆水利电力职业技术学院电力工程学院，重庆市永川区 402160

收稿日期:2025-01-07 修回日期:2025-03-19 出版日期:2026-02-28 发布日期:2026-02-12
通讯作者: 邸宏亮
作者简介:张萍(1979)，女，博士，副教授，研究方向为新能源电力系统建模与控制，415621328@qq.com；
邸宏亮(1997)，男，硕士，研究方向为储能在电力系统中的应用，本文通信作者，949228805@qq.com；
胡龙(2000)，男，硕士，研究方向为电力系统频率稳定性控制，1507418400@qq.com；
薛延刚(1973)，男，博士，教授，研究方向为流体机械故障诊断，xyg3024_cn@163.com；
刘海涛(1997)，男，硕士，研究方向为储能在电力系统中的应用，1609278754@qq.com。
基金资助:
国家自然科学基金项目(51867085)

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

Ping ZHANG¹, Hongliang DI¹, Long HU¹, Yangang XUE², Haitao LIU¹

^1.College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 733000, Gansu Province, China
^2.Technical College of Electric Power Engineering, Chongqing Water Resources and Electric Engineering College, Yongchuan District, Chongqing 402160, China

Received:2025-01-07 Revised:2025-03-19 Published:2026-02-28 Online:2026-02-12
Contact: Hongliang DI
Supported by:
National Natural Science Foundation of China(51867085)

摘要/Abstract

摘要：

目的针对电池储能辅助火电调频存在难以应对高幅、高频扰动的问题，提出一种基于分层自适应控制的混合储能参与二次调频控制策略。方法外层讨论系统剩余能量与比例因子之间的关系，提出基于数学函数方法的比例因子自适应控制策略，在系统当前调频能力的基础上合理分配区域控制信号；同时对内层机组与储能出力进行优化控制，使用变模糊PI控制机组出力，使用变时间常数低阶滤波的双层模糊控制储能出力，在保证储能不过充、过放的前提下，对调频信号进行自适应分配；并使用连续负荷扰动进行仿真分析。结果所提比例因子自适应控制策略相比传统定 $K$ 方法，最大频率偏差减少了2.2%，储能贡献电量降低了31.7%，储能荷电状态维持效果更好。结论所提控制策略可以优化系统频率控制，为维护电网频率安全提出新方法。

关键词: 混合储能, 火电机组, 二次调频, 控制策略, 自适应比例因子, 荷电状态, 系统剩余能量

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

中图分类号:

TK 01

张萍, 邸宏亮, 胡龙, 薛延刚, 刘海涛. 基于分层自适应控制的混合储能参与二次调频控制策略[J]. 发电技术, 2026, 47(1): 99-110.

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.

图/表 22

图1 区域互联系统二次调频模型

Fig. 1 Secondary frequency regulation model for regional interconnected systems

图2 火电机组出力的比例因子曲线

Fig. 2 Proportional factor curves of thermal power unit output

图3 混合储能SOC反馈的比例因子曲线

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

图4 自适应控制综合设计流程

Fig. 4 Comprehensive design process of adaptive control

图5 变模糊原理示意图

Fig. 5 Schematic diagram of variable fuzzy principle

图6 变模糊PI结构图

Fig. 6 Variable fuzzy PI structure

表1 比例参量ΔKp的模糊规则

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

表2 积分参量ΔKi的模糊规则

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

图7 变时间常数低阶滤波控制结构

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

表3 可变时间常数Ti模糊规则

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

表3 可变时间常数Ti模糊规则

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

图8 储能单元控制结构图

Fig. 8 Control structure of energy storage unit

表4 优化信号Ace,SF的模糊规则

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

表4 优化信号Ace,SF的模糊规则

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

表5 优化信号Ace,SB的模糊规则

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

表5 优化信号Ace,SB的模糊规则

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

图9 控制策略结构框架

Fig. 9 Framework of control strategy

表6 仿真参数

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

表6 仿真参数

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

图10 连续扰动负荷曲线

Fig. 10 Continuous disturbance load curve

图11 连续扰动负荷曲线下不同策略的响应曲线对比

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

表7 连续扰动负荷下不同策略的评价指标

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

表7 连续扰动负荷下不同策略的评价指标

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

图12 连续扰动负荷曲线下不同控制器的响应曲线对比

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

表8 连续扰动负荷下不同控制器的评价指标

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

表8 连续扰动负荷下不同控制器的评价指标

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

图13 连续扰动负荷曲线下不同控制方式的响应曲线对比

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

表9 连续扰动负荷下不同控制方式的评价指标

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

表9 连续扰动负荷下不同控制方式的评价指标

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

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基于分层自适应控制的混合储能参与二次调频控制策略

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

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