基于模糊控制算法的光储系统输出功率优化

doi:10.11930/j.issn.1004-9649.202406062

摘要/Abstract

摘要：

针对现有光储系统中多储能变流器功率分配问题，提出基于模糊控制算法的光储系统优化输出功率策略。依据储能变流器传输功率与电池健康特征量之间的关系，制定相应的模糊集合和隶属度函数；利用模糊控制算法，在储能单元温度低于或高于所设置的预警温度时，结合储能单元老化规律及储能单元健康因子系数，优化各储能单元功率分配，有效减少储能单元能量损耗及延长电池寿命。仿真结果表明，与传统的控制策略相比，在消耗相同的储能容量下，所提策略可减缓电池老化速度19.1%，并有效减缓储能单元温度的快速升高和能量损耗，整体上提高了光储系统安全和经济性。

关键词: 储能系统, 多储能变流器, 模糊控制, 储能单元预警温度, 电池寿命, 经济性

Abstract:

Aiming at the power allocation problem of multiple energy storage converters in existing photovoltaic and energy storage hybrid systems, an optimized output power strategy for photovoltaic and energy storage hybrid systems based on a fuzzy control algorithm is proposed. This strategy formulates corresponding fuzzy sets and membership functions based on the relationship between the transmission power of energy storage converters and the health characteristics of batteries. Using fuzzy control algorithm, when the temperature of the energy storage unit is lower than or higher than the preset warning temperature, the strategy combines the aging law and the health factor coefficient of the energy storage unit to optimize power distribution. This effectively reduces energy losses in the energy storage units and extends battery life. Simulation results show that, compared with traditional control strategies, the proposed strategy can slow down the aging rate of batteries by 19.1% under the same energy storage capacity consumption, and effectively mitigate the rapid temperature rise and energy loss of energy storage units. Overall, it enhances the safety and economy of the photovoltaic and energy storage hybrid system.

Key words: energy storage system, multiple energy storage converter, fuzzy control, warning temperature of the energy storage unit, battery life, economy

肖湘奇, 邹晟, 贺星, 肖建红, 马斌. 基于模糊控制算法的光储系统输出功率优化[J]. 中国电力, 2025, 58(6): 67-75.

XIAO Xiangqi, ZOU Sheng, HE Xing, XIAO Jianhong, MA Bin. Output Power Optimization of Photovoltaic and Energy Storage Hybrid System Based on Fuzzy Control Algorithm[J]. Electric Power, 2025, 58(6): 67-75.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202406062

https://www.electricpower.com.cn/CN/Y2025/V58/I6/67

图/表 11

参考文献 31

1	夏向阳, 谭欣欣, 单周平, 等. 储能电站锂离子电池本体安全关键技术及新技术应用情况[J]. 中国电力, 2024, 57 (11): 1- 17.
	XIA Xiangyang, TAN Xinxin, SHAN Zhouping, et al. Key technology and development prospect of ontology safety for lithium-ion battery storage power stations[J]. Electric Power, 2024, 57 (11): 1- 17.
2	朱沐雨, 马宏忠, 郭鹏宇, 等. 典型调峰/调频工况下储能电池组荷电状态估计[J]. 中国电力, 2024, 57 (6): 18- 26.
	ZHU Muyu, MA Hongzhong, GUO Pengyu, et al. State of charge estimation of energy storage battery pack under typical peak/frequency modulation conditions[J]. Electric Power, 2024, 57 (6): 18- 26.
3	和萍, 刘鑫, 宫智杰, 等. 高比例可再生能源电力系统源荷储联合调峰分层优化运行[J]. 电力系统保护与控制, 2024, 52 (18): 112- 122.
	HE Ping, LIU Xin, GONG Zhijie, et al. Hierarchical optimization operation model for joint peak-load regulation of source-load-storagein a high proportion of renewable energy power system[J]. Power System Protection and Control, 2024, 52 (18): 112- 122.
4	郑涛, 孟令昆, 强雨泽, 等. 计及SOC影响的电化学储能系统低电压穿越控制策略[J]. 电力系统保护与控制, 2024, 52 (13): 171- 178.
	ZHENG Tao, MENG Lingkun, QIANG Yuzhe, et al. Low voltage ride through control strategy for electrochemical energy storage system considering SOC influence[J]. Power System Protection and Control, 2024, 52 (13): 171- 178.
5	贺悝, 郭罗权, 谭庄熙, 等. 高比例新能源电网中储能调频死区优化设定控制策略[J]. 电力系统保护与控制, 2024, 52 (18): 65- 75.
	HE Li, GUO Luoquan, TAN Zhuangxi, et al. Improved dead zone setting of a frequency regulation strategy for energy storage with high penetration of RESs[J]. Power System Protection and Control, 2024, 52 (18): 65- 75.
6	孙建华, 王佳旭, 杜晓勇, 等. 考虑频率安全约束的高比例风电电力系统储能优化配置策略[J]. 电力科学与技术学报, 2024, 39 (5): 151- 162.
	SUN Jianhua , WANG Jiaxu, DU Xiaoyong, et al. Optimization strategy for energy storage configuration in high proportion wind power system considering frequency safety constraints[J]. Journal of Electric Power Science and Technology, 2024, 39 (5): 151- 162.
7	鲁志远, 刘世林, 范保程, 等. 含广域混合储能互联电力系统的负荷频率控制[J]. 电力科学与技术学报, 2023, 38 (6): 96- 104.
	LU Zhiyuan, LIU Shilin, FAN Baocheng, et al. Load frequency control of interconnected power system with wide-area hybrid energy storage[J]. Journal of Electric Power Science and Technology, 2023, 38 (6): 96- 104.
8	郑明才, 罗治军, 尹强等. 面向直流操作电源系统的LiFePO4电池性能优化控制研究[J]. 电源学报, 2023, 21 (1): 159- 167.
	ZHENG Mingcai, LUO Zhijun, YIN Qiang, et al. Optimal control of LiFePO4 battery performance for DC operating power systems[J]. Journal of Power Supply, 2023, 21 (1): 159- 167.
9	岳家辉, 夏向阳, 蒋戴宇, 等. 基于电压数据片段混合模型的锂离子电池剩余寿命预测与健康状态估计[J]. 中国电力, 2023, 56 (7): 163- 174.
	YUE Jiahui, XIA Xiangyang, JIANG Daiyu, et al. Remaining useful life prediction and state of health estimation of lithium-ion batteries based on voltage data segment hybrid model[J]. Electric Power, 2023, 56 (7): 163- 174.
10	夏向阳, 陈贵全, 刘俊翔, 等. 储能系统直流侧纹波电流对锂离子电池寿命影响分析及优化控制策略[J]. 电工技术学报, 2023, 38 (22): 6218- 6229.
	XIA Xiangyang, CHEN Guiquan, LIU Junxiang, et al. Analysis and optimization control strategy of the impact of DC ripple current on the lifespan of lithium-ion batteries in energy storage systems[J]. Journal of Electrical Engineering, 2023, 38 (22): 6218- 6229.
11	彭昊, 罗正经, 夏向阳, 等. 储能系统多电池簇健康状态均衡控制策略[J]. 中国电力, 2024, 57 (6): 45- 52.
	PENG Hao, LUO Zhengjing, XIA Xiangyang, et al. Health state balance control strategy for multi battery clusters in energy storage systems[J]. Electric Power, 2024, 57 (6): 45- 52.
12	LI X N, GENG G C, JIANG Q Y, et al. Consensus-based multi-converter power allocation strategy in battery energy storage system[J]. Journal of Energy Storage, 2023, 60, 106623. DOI
13	LI X N, LYU L X, GENG G C, et al. Power allocation strategy for battery energy storage system based on cluster switching[J]. IEEE Transactions on Industrial Electronics, 2022, 69 (4): 3700- 3710. DOI
14	霍俊达, 王毅. 兼顾平抑波动与储能保护的混合储能优化策略[J/OL]. 华北电力大学学报(自然科学版), 1−12[2024-08-14]. http://kns.cnki.net/kcms/detail/13.1212.tm.20240612.1415.002.html.
	HUO Junda, WANG Yi. Hybrid energy storage optimization strategy that balances smoothing fluctuations and energy storage protection[J/OL]. Journal of North China Electric Power University (Natural Science Edition), 1−12 [2024-08-14]. http://kns.cnki.net/kcms/detail/13.1212.tm.20240612.1415.002.html.
15	林莉, 林雨露, 谭惠丹, 等. 计及SOC自恢复的混合储能平抑风电功率波动控制[J]. 电工技术学报, 2024, 39 (3): 658- 671.
	LIN Li, LIN Yulu, TAN Huidan, et al. Hybrid energy storage control with SOC self-recovery to smooth out wind power fluctuations[J]. Transactions of China Electrotechnical Society, 2024, 39 (3): 658- 671.
16	余洋, 王卜潇, 吴玉威, 等. 面向光伏平抑考虑SOH与SOC的电池储能系统功率分配方法[J]. 太阳能学报, 2024, 45 (3): 377- 388.
	YU Yang, WANG Buxiao, WU Yuwei, et al. Power allocation method for battery energy storage systems considering SOH and SOC for photovoltaic stabilization[J]. Acta Energiae Solaris Sinica, 2024, 45 (3): 377- 388.
17	李建林, 李雅欣, 刘海涛, 等. 计及储能电站安全性的功率分配策略研究[J]. 电工技术学报, 2022, 37 (23): 5976- 5986.
	LI Jianlin, LI Yaxin, LIU Haitao, et al. Research on power distribution strategy considering the safety of energy storage power station[J]. Transactions of China Electrotechnical Society, 2022, 37 (23): 5976- 5986.
18	TREMBLAY O, DESSAINT L A. Experimental validation of a battery dynamic model for EV applications[J]. World Electric Vehicle Journal, 2009, 3 (2): 289- 298. DOI
19	OMAR N, ABDEL MONEM M, FIROUZ Y, et al. Lithium iron phosphate based battery–Assessment of the aging parameters and development of cycle life model[J]. Applied Energy, 2014, 113, 1575- 1585. DOI
20	Simulink: Generic battery model[EB/OL]. https://www.mathworks.com/help/releases/R2022a/physmod/sps/powersys/ref/battery.html.
21	王聪聪, 叶思成, 裴春兴, 等. 电池健康状态实验与评估方法综述[J]. 电池, 2021, 51 (2): 197- 200.
	WANG Congcong, YE Sicheng, PEI Chunxing, et al. Review on battery state-of-health experiment and estimation methods[J]. Battery Bimonthly, 2021, 51 (2): 197- 200.
22	黎冲, 王成辉, 王高, 等. 基于数据驱动的锂离子电池健康状态估计技术[J]. 中国电力, 2022, 55 (8): 73- 86, 95.
	LI Chong, WANG Chenghui, WANG Gao, et al. Technology of lithium-ion battery state-of-health assessment based on data-driven[J]. Electric Power, 2022, 55 (8): 73- 86, 95.
23	VETTER J, NOVÁK P, WAGNER M R, et al. Ageing mechanisms in lithium-ion batteries[J]. Journal of Power Sources, 2005, 147 (1/2): 269- 281.
24	CHANG L J, CHEN W Y, MAO Z Y, et al. Experimental study on the effect of ambient temperature and discharge rate on the temperature field of prismatic batteries[J]. Journal of Energy Storage, 2023, 59, 106577. DOI
25	BESSMAN A, SOARES R, WALLMARK O, et al. Aging effects of AC harmonics on lithium-ion cells[J]. Journal of Energy Storage, 2019, 21, 741- 749. DOI
26	BALA S, TENGNÉR T, ROSENFELD P, et al. The effect of low frequency current ripple on the performance of a Lithium Iron Phosphate (LFP) battery energy storage system[C]//2012 IEEE Energy Conversion Congress and Exposition (ECCE). Raleigh, NC, USA. IEEE, 2012: 3485−3492.
27	BRAND M J, HOFMANN M H, SCHUSTER S S, et al. The influence of current ripples on the lifetime of lithium-ion batteries[J]. IEEE Transactions on Vehicular Technology, 2018, 67 (11): 10438- 10445. DOI
28	张雪. 非隔离型光伏并网逆变器高效MPPT控制方法研究[D]. 广州: 华南理工大学, 2012.
	ZHANG Xue. Study of high efficiency MPPT control method of non-isolated grid-connected PV inverter[D]. Guangzhou: South China University of Technology, 2012.
29	张思章. 高频隔离型并网逆变器的研制[D]. 广州: 华南理工大学, 2012.
	ZHANG Sizhang. Development of high frequency isolated grid-connected inverter[D]. Guangzhou: South China University of Technology, 2012.
30	茆书睿, 李熹宁. 基于电池状态的储能电站集群调度策略[J]. 太阳能学报, 2023, 44 (8): 54- 61.
	MAO Shurui, LI Xining. Cluster dispatch strategy for energy storage power station based on battery state[J]. Acta Energiae Solaris Sinica, 2023, 44 (8): 54- 61.
31	朱晔, 兰贞波, 隗震, 等. 考虑碳排放成本的风光储多能互补系统优化运行研究[J]. 电力系统保护与控制, 2019, 47 (10): 127- 133.
	ZHU Ye, LAN Zhenbo, WEI Zhen, et al. Research on optimal operation of wind-PV-ES complementary system considering carbon emission cost[J]. Power System Protection and Control, 2019, 47 (10): 127- 133.

参数	数值	参数	数值
储能直流侧电压/V	800	PCS额定运行功率/kW	15
电网电压/V	380	PCS转换功率下限/kW	6
储能交流侧电感/mH	21	S_OH1/%	95
S_OH2/%	90	S_OH3/%	85

参数	数值	参数	数值
储能直流侧电压/V	800	PCS额定运行功率/kW	15
电网电压/V	380	PCS转换功率下限/kW	6
储能交流侧电感/mH	21	S_OH1/%	95
S_OH2/%	90	S_OH3/%	85

控制策略	场景	P_ref/ kW	THD/ %	P_batt1/ kW	P_batt2/ kW	P_batt3/ kW	I_dc1/ A	I_dc2/ A	I_dc3/ A	消耗电池额定容量160% 下的老化循环圈数
本文控制策略	1	15	2.50	7.70	7.30	0.0	18.0	17.0	0.0	0.6980
	2	18	2.30	9.30	8.70	0.0	21.7	20.3	0.0	0.7390
	3	23	2.54	8.13	7.67	7.2	19.2	18.0	16.8	0.7040
	4	30	2.23	10.60	10.00	9.4	24.7	23.3	21.9	0.7620
	5	42	1.45	14.80	14.00	13.2	34.6	32.7	30.7	0.8471
传统控制策略	1	15	1.31	15.00	0.00	0.0	35.0	0.0	0.0	0.862 5
	2	18	1.94	15.00	3.00	0.0	35.0	7.0	0.0	0.808 9
	3	23	1.63	15.00	8.00	0.0	35.0	19.0	0.0	0.813 1
	4	30	1.32	15.00	15.00	0.0	35.0	35.0	0.0	0.8625
	5	42	1.46	15.00	15.00	12.0	35.0	35.0	28.0	0.8433

控制策略	场景	P_ref/ kW	THD/ %	P_batt1/ kW	P_batt2/ kW	P_batt3/ kW	I_dc1/ A	I_dc2/ A	I_dc3/ A	消耗电池额定容量160% 下的老化循环圈数
本文控制策略	1	15	2.50	7.70	7.30	0.0	18.0	17.0	0.0	0.6980
	2	18	2.30	9.30	8.70	0.0	21.7	20.3	0.0	0.7390
	3	23	2.54	8.13	7.67	7.2	19.2	18.0	16.8	0.7040
	4	30	2.23	10.60	10.00	9.4	24.7	23.3	21.9	0.7620
	5	42	1.45	14.80	14.00	13.2	34.6	32.7	30.7	0.8471
传统控制策略	1	15	1.31	15.00	0.00	0.0	35.0	0.0	0.0	0.862 5
	2	18	1.94	15.00	3.00	0.0	35.0	7.0	0.0	0.808 9
	3	23	1.63	15.00	8.00	0.0	35.0	19.0	0.0	0.813 1
	4	30	1.32	15.00	15.00	0.0	35.0	35.0	0.0	0.8625
	5	42	1.46	15.00	15.00	12.0	35.0	35.0	28.0	0.8433

名称	参数	名称	参数
电池类型	LiNiMnCoO₂	电池规格	2.2 mg*180(mA·h·g^–1)
充电截止电压/V	4.3	放电截止电压/V	2.5
在C/5下的标称容量/(mA·h)	0.4	电压保护上限/V	5
电压保护下限/V	0.5	脉冲精度/ms	1
恒温箱温度/℃	30