A frequency-modulation power optimization method for energy storage power stations considering the transition state of charge-discharge and power constraints

doi:10.19799/j.cnki.2095-4239.2024.1191

Abstract

Abstract:

Frequent charge-discharge cycles reduce the service life of energy storage power stations, and the transmission power of energy storage units connected to the power conversion system (PCS) may become too low, violating national energy management grid connection standards. To address this issue, this study proposes a frequency-modulation power optimization method for energy storage power stations that considers the transition state of charge-discharge and power constraints. This method divides the unit group into charging and discharging groups to meet their respective requirements. While ensuring that the alternating current (AC) power of the corresponding PCS does not fall below a set lower limit during energy storage unit output, each unit in the charging and discharging groups is dynamically updated based on the automatic generation control (AGC) instruction. This reduces the number of charge-discharge state transitions. Compared with traditional allocation strategies, the proposed strategy lowers frequency modulation costs and charge-discharge conversion frequency and ensures compliance with national grid connection standards by preventing the corresponding PCS AC side power from exceeding its limit during energy storage unit operation.

Key words: energy storage unit, AGC, frequency modulation cost, charge and discharge conversion, power constraint, distribution optimization

CLC Number:

TM 911

Liqiang SUN, Shaojia DANG, Gang LIU, Shenyou WANG, Pengfei HU. A frequency-modulation power optimization method for energy storage power stations considering the transition state of charge-discharge and power constraints[J]. Energy Storage Science and Technology, 2025, 14(3): 1286-1298.

Figures/Tables 16

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Table 1

Table 2

Fig. 6

Fig. 7

Table 3

Table 4

Fig. 8

Fig. 9

Fig. 10

Table 5

Table 6

References 20

1	袁威. 低碳经济背景下新能源行业发展现状分析[J]. 储能科学与技术, 2023, 12(11): 3589-3590.
	YUAN W. Analysis on the development status of new energy industry under the background of low-carbon economy[J]. Energy Storage Science and Technology, 2023, 12(11): 3589-3590.
2	周凡宇, 曾晋珏, 王学斌. 碳中和目标下电化学储能技术进展及展望[J]. 动力工程学报, 2024, 44(3): 396-405. DOI: 10.19805/j.cnki.jcspe.2024.230571.
	ZHOU F Y, ZENG J J, WANG X B. Progress and prospect of electrochemical energy storage for carbon neutralization[J]. Journal of Chinese Society of Power Engineering, 2024, 44(3): 396-405. DOI: 10.19805/j.cnki.jcspe.2024.230571.
3	魏文荣, 苗世洪, 王廷涛, 等. 计及储能电站荷电状态恢复和调整的电力系统调频指令最优分配方法[J]. 中国电机工程学报, 2024, 44(S1): 53-65. DOI: 10.13334/j.0258-8013.pcsee.232754.
	WEI W R, MIAO S H, WANG T T, et al. Optimal distribution method for frequency regulation commands considering the state of charge recovery and adjustment[J]. Proceedings of the CSEE, 2024, 44(S1): 53-65. DOI: 10.13334/j.0258-8013.pcsee.232754.
4	WEN Y L, HU Z C, CHEN X L, et al. Centralized distributionally robust chance-constrained dispatch of integrated transmission-distribution systems[J]. IEEE Transactions on Power Systems, 2024, 39(2): 2947-2959. DOI: 10.1109/TPWRS.2023.3318515.
5	赵冬梅, 徐辰宇, 陶然, 等. 多元分布式储能在新型电力系统配电侧的灵活调控研究综述[J]. 中国电机工程学报, 2023, 43(5): 1776-1798. DOI: 10.13334/j.0258-8013.pcsee.220778.
	ZHAO D M, XU C Y, TAO R, et al. Review on flexible regulation of multiple distributed energy storage in distribution side of new power system[J]. Proceedings of the CSEE, 2023, 43(5): 1776-1798. DOI: 10.13334/j.0258-8013.pcsee.220778.
6	ZHAO T Q, PARISIO A, MILANOVIĆ J V. Distributed control of battery energy storage systems for improved frequency regulation[J]. IEEE Transactions on Power Systems, 2020, 35(5): 3729-3738. DOI: 10.1109/TPWRS.2020.2974026.
7	STÜDLI S, CORLESS M, MIDDLETON R H, et al. On the AIMD algorithm under saturation constraints[J]. IEEE Transactions on Automatic Control, 2017, 62(12): 6392-6398. DOI: 10.1109/TAC.2017.2651160.
8	杨伟峰. 风电和储能参与的层次协调频率控制方法研究[D]. 长沙: 湖南大学, 2022. DOI: 10.27135/d.cnki.ghudu.2022.004312.
	YANG W F. Research on hierarchical coordinated frequency control method involving wind power and energy storage[D]. Changsha: Hunan University, 2022. DOI: 10.27135/d.cnki.ghudu.2022.004312.
9	李军徽, 宋清龙, 郭琦, 等. 计及可用容量和调频成本的网侧多储能电站双层优化策略[J/OL]. 电力系统自动化, 2024: 1-17. (2024-07-29). https://kns.cnki.net/kcms/detail/32.1180.TP.20240726. 1159.002.html.
	LI J H, SONG Q L, GUO Q, et al. Bi-level optimization strategy of grid-side multi-energy storage power station considering available capacity and frequency modulation cost[J/OL]. Automation of Electric Power Systems, 2024: 1-17. (2024-07-29). https://kns.cnki.net/kcms/detail/32.1180.TP.20240726.1159.002.html.
10	孙秦峰, 李凤婷, 王森, 等. 提升风电场有功调节能力的风储系统多时间尺度运行策略[J]. 电力系统保护与控制, 2023, 51(9): 21-31. DOI: 10.19783/j.cnki.pspc.221425.
	SUN Q F, LI F T, WANG S, et al. Multi-timescale operation strategy of a wind storage system to enhance the active regulation capacity of wind farms[J]. Power System Protection and Control, 2023, 51(9): 21-31. DOI: 10.19783/j.cnki.pspc.221425.
11	陆秋瑜, 胡伟, 闵勇, 等. 考虑时间相关性的风储系统多模式协调优化策略[J]. 电力系统自动化, 2015, 39(2): 6-12. DOI: 10.7500/AEPS20140922004.
	LU Q Y, HU W, MIN Y, et al. A multi-pattern coordinated optimization strategy of wind power and energy storage system considering temporal dependence[J]. Automation of Electric Power Systems, 2015, 39(2): 6-12. DOI: 10.7500/AEPS20140922004.
12	宋海明, 余中平, 关洪浩, 等. 面向发电计划跟踪与调峰的新能源汇集系统储能协调运行策略[J/OL]. 现代电力, 1-18. [2024-12-09]. https://doi.org/10.19725/j.cnki.1007-2322.2023.0395.
	SONG H M, YU Z P, GUAN H J, et al. Coordinated operation strategy of new energy collection system for power generation planning tracking and peak load balancing[J/OL]. Modern Electric Power, 1-18. [2024-12-09]. https://doi.org/10.19725/j.cnki.1007-2322.2023.0395.
13	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. DOI: 10.11930/j.issn.1004-9649.202401124
	PENG H, LUO Z J, XIA X Y, et al. Health state equalization control strategy for multi-battery clusters in energy storage systems[J]. Electric Power, 2024, 57(6): 45-52. DOI: 10.11930/j.issn.1004-9649.202401124
14	严干贵, 刘莹, 段双明, 等. 电池储能单元群参与电力系统二次调频的功率分配策略[J]. 电力系统自动化, 2020, 44(14): 26-34. DOI: 10.7500/AEPS20200116008.
	YAN G G, LIU Y, DUAN S M, et al. Power distribution strategy for battery energy storage unit group participating in secondary frequency regulation of power system[J]. Automation of Electric Power Systems, 2020, 44(14): 26-34. DOI: 10.7500/AEPS20200116008.
15	HE G N, CHEN Q X, KANG C Q, et al. Optimal bidding strategy of battery storage in power markets considering performance-based regulation and battery cycle life[J]. IEEE Transactions on Smart Grid, 2016, 7(5): 2359-2367. DOI: 10.1109/TSG. 2015.2424314.
16	陆秋瑜, 胡伟, 闵勇, 等. 集群风储联合系统广域协调优化控制[J]. 中国电机工程学报, 2014, 34(19): 3132-3140. DOI: 10.13334/j.0258-8013.pcsee.2014.19.012.
	LU Q Y, HU W, MIN Y, et al. Wide-area coordinated optimization control of cluster wind-ESS integrated systems[J]. Proceedings of the CSEE, 2014, 34(19): 3132-3140. DOI: 10.13334/j.0258-8013.pcsee.2014.19.012.
17	林莉, 金鑫, 朱丽云, 等. 考虑充放电能量不均衡的双电池系统状态评估与控制策略[J]. 电力系统自动化, 2018, 42(10): 128-134. DOI: 10.7500/AEPS20171107013.
	LIN L, JIN X, ZHU L Y, et al. State evaluation and control strategy of dual-battery system considering unbalance of charging and discharging energy[J]. Automation of Electric Power Systems, 2018, 42(10): 128-134. DOI: 10.7500/AEPS20171107013.
18	李军徽, 侯涛, 严干贵, 等. 计及调频成本和荷电状态恢复的多储能系统调频功率双层优化[J]. 中国电机工程学报, 2021, 41(23): 8020-8032. DOI: 10.13334/j.0258-8013.pcsee.202553.
	LI J H, HOU T, YAN G G, et al. Two-layer optimization of frequency modulation power in multi-battery energy storage system considering frequency modulation cost and recovery of state of charge[J]. Proceedings of the CSEE, 2021, 41(23): 8020-8032. DOI: 10.13334/j.0258-8013.pcsee.202553.
19	胡泽春, 夏睿, 吴林林, 等. 考虑储能参与调频的风储联合运行优化策略[J]. 电网技术, 2016, 40(8): 2251-2257. DOI: 10.13335/j.1000-3673.pst.2016.08.001.
	HU Z C, XIA R, WU L L, et al. Joint operation optimization of wind-storage union with energy storage participating frequency regulation[J]. Power System Technology, 2016, 40(8): 2251-2257. DOI: 10.13335/j.1000-3673.pst.2016.08.001.
20	李翠萍, 司文博, 李军徽, 等. 基于集合经验模态分解和多目标遗传算法的火-多储系统调频功率双层优化[J]. 电工技术学报, 2024, 39(7): 2017-2032.
	LI C P, SI W B, LI J H, et al. Bi-level optimization of frequency modulation power of fire-multi-storage system based on set empirical mode decomposition and multi-objective genetic algorithm[J]. China Industrial Economics, 2024, 39(7): 2017-2032.

参数	储能单元
额定功率/MW	10
额定容量/MWh	20
单位功率费用/(元/kWh)	500^[12]
单位容量费用/(元/kWh)	1500^[12]
单位功率运行维护费用/(元/kWh)	20^[12]
残差值	0.05^[12]
报废率	0.2^[12]

参数	单元1	单元2	单元3	单元4	单元5	单元6
SOC	0.7	0.65	0.6	0.4	0.35	0.3
充放电效率	0.98	0.95	0.92	0.98	0.95	0.92
充放电状态	放电	放电	放电	充电	充电	充电

策略	调频里程/MW	出力偏差/MW
策略1	612.724	4.276
策略3	594.838	22.162
策略4	591.467	25.533

成本	策略1	策略3	策略4
循环成本/万元	8.4262	10.3532	8.2107
转换成本/万元	0.6974	0.7960	0.6891
总和/万元	9.1237	11.1492	8.8998

参数	单元1	单元2	单元3	单元4	单元5	单元6
SOC	0.2	0.2	0.2	0.8	0.8	0.8
充放电状态	放电	放电	放电	充电	充电	充电