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1.中国移动通信集团设计院有限公司,北京 100080
2.清华大学电机工程与应用电子技术系,北京 100084
Received:14 January 2026,
Revised:2026-02-28,
Published:28 June 2026
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刘宝昌, 张珺玮, 徐峰, 等. 考虑寿命损耗与SOC均衡的分层-分布式储能聚合控制策略[J]. 储能科学与技术, 2026, 15(6): 2355-2367.
LIU Baochang, ZHANG Junwei, XU Feng, et al. Hierarchical-distributed aggregation control strategy for energy storage considering lifetime degradation and SOC balancing[J]. Energy Storage Science and Technology, 2026, 15(6): 2355-2367.
刘宝昌, 张珺玮, 徐峰, 等. 考虑寿命损耗与SOC均衡的分层-分布式储能聚合控制策略[J]. 储能科学与技术, 2026, 15(6): 2355-2367. DOI: 10.19799/j.cnki.2095-4239.2026.0039.
LIU Baochang, ZHANG Junwei, XU Feng, et al. Hierarchical-distributed aggregation control strategy for energy storage considering lifetime degradation and SOC balancing[J]. Energy Storage Science and Technology, 2026, 15(6): 2355-2367. DOI: 10.19799/j.cnki.2095-4239.2026.0039.
随着可再生能源大规模接入,储能在提升电力系统灵活性、平抑负荷波动及保障系统运行安全等方面发挥重要作用。针对分布式储能单元在容量规模、功率等级、荷电状态(state of charge,SOC)及健康状态(state of health,SOH)等方面的多维差异,提出了一种面向储能集群的分层-分布式聚合控制策略。首先,基于自适应滤波算法,实现动态工况和测量噪声不确定条件下的储能单元高精度状态估计,并构建储能可调度能力模型。其次,提出分层储能聚合控制架构,上层采用集中优化策略,以运行经济性和负荷平滑为双重目标,求解储能集群最优聚合功率响应;下层采用分布式协调控制方法,将储能单元SOC均衡与寿命损耗成本纳入加权分配机制,实现各储能单元功率的动态协调分配。以某区域夏季典型日负荷为例开展仿真分析,结果表明,该聚合控制策略能够有效平抑电网负荷波动并获取电价差收益,日最大负荷由2 MW降至1.568 MW,负荷峰谷差从1.35 MW减小至0.669 MW。且在满足系统功率响应需求的同时,能有效抑制储能单元间的状态不一致以及健康差异的扩展,单体SOC方差较传统方案降低50%,寿命损耗成本降低2%。所提方法对提升储能系统的整体运行效率与全生命周期健康水平具有重要意义。
Energy storage systems assume a pivotal role in the large-scale integration of renewable energy
enhancing the flexibility of power systems
mitigating load fluctuations
and ensuring operational security. This paper proposes a hierarchical-distributed aggregation control strategy for energy storage clusters
in response to the multidimensional differences among energy storage units in terms of capacity
power
State of Charge
and State of Health. First
an adaptive filtering algorithm is employed to attain high-precision state estimation of energy storage units under dynamic operating conditions and uncertain measurement noise. Subsequently
a dispatchable capability model for energy storage is constructed. Secondly
a hierarchical control architecture is proposed. The upper layer employs a centralized optimization to determine the optimal power response of the energy storage cluster
with operational economy and load smoothing as dual objectives. The lower layer implements a distributed coordinated control scheme
incorporating unit SOC balancing and life cost into a weighted allocation mechanism to achieve dynamic and coordinated power dispatch among energy storage units. A simulation is conducted to assess the load of a specific region on a typical summer day. The findings indicate that the proposed aggregation control strategy can effectively mitigate grid load fluctuations and capture benefits from electricity price differences. Daily peak load was reduced from 2 to 1.568 MW
and the peak-valley load difference was decreased from 1.35 MW to 0.669 MW. Furthermore
while satisfying the power response requirements of the system
it effectively mitigates the propagation of state inconsistencies and health disparities among storage units
thereby reducing the variance of SOC by 50% and life cost by 2% in comparison with conventional methods. The proposed method exhibits considerable significance in terms of enhancing the overall operational efficiency and promoting the full lifecycle health of the energy storage system.
刘海丞, 王旭阳, 李红军, 等. 面向分布式光伏消纳的需求侧灵活资源与输配协同规划[J]. 电力建设, 2025, 46(10): 58-72. DOI:10.12204/j.issn.1000-7229.2025.10.006.
LIU H C, WANG X Y, LI H J, et al. Multiple flexible resources and transmission and distribution collaborative planning for distributed PV consumption[J]. Electric Power Construction, 2025, 46(10): 58-72. DOI:10.12204/j.issn.1000-7229.2025.10.006.
陈郑平, 李文忠, 陈飞雄, 等. 分布式资源助力新型电力系统灵活性提升研究综述[J]. 电力工程技术, 2025, 44(2): 145-159. DOI:10.12158/j.2096-3203.2025.02.014.
CHEN Z P, LI W Z, CHEN F X, et al. Summary of research on improving the flexibility of new power systems with distributed resources[J]. Jiangsu Electrical Engineering, 2025, 44(2): 145-159. DOI:10.12158/j.2096-3203.2025.02.014.
张媛一, 刘震宇, 孟继军, 等. 分布式光伏储能系统的优化配置与运行控制研究[J]. 储能科学与技术, 2025, 14(10): 3917-3919.
ZHANG Y Y, LIU Z Y, MENG J J, et al. Research on the optimal configuration and operation control of distributed photovoltaic energy storage systems[J]. Energy Storage Science and Technology, 2025, 14(10): 3917-3919.
ZHAO D, XU C, 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): 1776-1799.
ZHANG D, SHAFIULLAH G M, DAS C K, et al. A systematic review of optimal planning and deployment of distributed generation and energy storage systems in power networks[J]. Journal of Energy Storage, 2022, 56: 105937. DOI:10.1016/j.est.2022.105937.
张世旭, 李姚旺, 刘伟生, 等. 面向微电网群的云储能经济-低碳-可靠多目标优化配置方法[J]. 电力系统自动化, 2024, 48(1): 21-30.
ZHANG S X, LI Y W, LIU W S, et al. Economic, low-carbon and reliable multi-objective optimal configuration method of cloud energy storage for microgrid clusters[J]. Automation of Electric Power Systems, 2024, 48(1): 21-30.
蔡福霖, 胡泽春, 曹敏健, 等. 提升新能源消纳能力的集中式与分布式电池储能协同规划[J]. 电力系统自动化, 2022, 46(20): 23-32. DOI:10.7500/AEPS20220331010.
CAI F L, HU Z C, CAO M J, et al. Coordinated planning of centralized and distributed battery energy storage for improving renewable energy accommodation capability[J]. Automation of Electric Power Systems, 2022, 46(20): 23-32. DOI:10.7500/AEPS20220331010.
张亮亮. 基于多智能体一致性理论的智能电网内分布式储能系统自治控制方法[J]. 高压电器, 2024, 60(8): 230-237, 258. DOI:10.13296/j.1001-1609.hva.2024.08.027.
ZHANG L L. Autonomous control method for distributed energy storage system in smart grid based on multi-agent consistency theory[J]. High Voltage Apparatus, 2024, 60(8): 230-237, 258. DOI:10.13296/j.1001-1609.hva.2024.08.027.
梁海峰, 丁政, 李鹏. 基于改进一致性算法的孤岛直流微电网储能系统分布式控制策略[J]. 电力系统保护与控制, 2023, 51(16): 59-71. DOI:10.19783/j.cnki.pspc.230115.
LIANG H F, DING Z, LI P. Distributed control strategy of an energy storage system in an isolated DC microgrid based on an improved consensus algorithm[J]. Power System Protection and Control, 2023, 51(16): 59-71. DOI:10.19783/j.cnki.pspc.230115.
彭大健, 肖浩, 裴玮, 等. 基于ADMM的共享储能参与电网辅助服务的分布式优化模型[J]. 电力自动化设备, 2024, 44(2): 1-8.
PENG D J, XIAO H, PEI W, et al. Distributed optimization model of shared energy storage participating in power grid auxiliary service based on ADMM[J]. Electric Power Automation Equipment, 2024, 44(2): 1-8.
张颖, 寇凌峰, 季宇, 等. 计及储能与分布式电源协同的配电网分层分区优化控制[J]. 中国电力, 2021, 54(2): 104-112.
ZHANG Y, KOU L F, JI Y, et al. Hierarchical and partitioned optimal control of distribution networks considering the coordination between energy storage and distributed generation systems[J]. Electric Power, 2021, 54(2): 104-112.
李军徽, 马得轩, 朱星旭, 等. 基于ADMM算法的主动配电网分层优化经济调度[J]. 电力建设, 2022, 43(8): 76-86.
LI J H, MA D X, ZHU X X, et al. Multi-level optimization of economic dispatching based on ADMM algorithm for active distribution network[J]. Electric Power Construction, 2022, 43(8): 76-86.
米阳, 王晓敏, 钱翌明, 等. 考虑通信时延的直流微电网分布式储能单元协调控制[J]. 电力系统保护与控制, 2022, 50(24): 91-100.
MI Y, WANG X M, QIAN Yuming, et al. Coordinated control method of distributed energy storage units in a DC microgrid considering communication delay[J]. Power System Protection and Control, 2022, 50(24): 91-100.
GU J P, YANG X D, ZHANG Y B, et al. Fuzzy droop control for SOC balance and stability analysis of DC microgrid with distributed energy storage systems[J]. Journal of Modern Power Systems and Clean Energy, 2024, 12(4): 1203-1216. DOI:10.35833/MPCE.2023.000119.
张天海, 杨小龙, 周帅, 等. 考虑储能SOC的分布式光伏一次调频优化控制方法[J]. 储能科学与技术, 2025, 14(10): 3796-3807. DOI:10.19799/j.cnki.2095-4239.2025.0295.
ZHANG T H, YANG X L, ZHOU S, et al. Optimization control method for distributed photovoltaic primary frequency regulation considering energy storage SOC[J]. Energy Storage Science and Technology, 2025, 14(10): 3796-3807. DOI:10.19799/j.cnki.2095-4239.2025.0295.
刘根才, 陆志欣, 杨智诚, 等. 考虑SOC均衡的分布式储能聚合控制方法[J]. 电力电容器与无功补偿, 2020, 41(3): 174-181. DOI:10.14044/j.1674-1757.pcrpc.2020.03.028.
LIU G C, LU Z X, YANG Z C, et al. Distributed energy storage aggregation control method considering SOC equalization[J]. Power Capacitor & Reactive Power Compensation, 2020, 41(3): 174-181. DOI:10.14044/j.1674-1757.pcrpc.2020.03.028.
贺悝, 谭庄熙, 李欣然, 等. 考虑荷电状态一致性的分布式储能电站一次调频控制策略[J]. 高电压技术, 2024, 50(2): 902-913. DOI:10.13336/j.1003-6520.hve.20221884.
HE K, TAN Z X, LI X R, et al. Control strategy of primary frequency regulation for distributed energy storage stations considering SOC consensus[J]. High Voltage Engineering, 2024, 50(2): 902-913. DOI:10.13336/j.1003-6520.hve.20221884.
李飞, 刘添一, 朱芯乐, 等. 基于SOC均衡误差补偿的分布式储能系统非线性控制方法[J]. 电网与清洁能源, 2025, 41(11): 123-130. DOI:10.26963/j.psce.2025.11015.
LI F, LIU T Y, ZHU X (L /Y), et al. The nonlinear control method of the distributed energy storage system based on SOC balancing error analysis[J]. Power System and Clean Energy, 2025, 41(11): 123-130. DOI:10.26963/j.psce.2025.11015.
ALRUMAYH O, WONG S, BHATTACHARYA K. Inclusion of battery SoH estimation in smart distribution planning with energy storage systems[J]. IEEE Transactions on Power Systems, 2021, 36(3): 2323-2333. DOI:10.1109/TPWRS.2020.3036448.
丰俊杰, 曾平良, 李亚楼, 等. 考虑充放电策略对储能寿命影响的新型分布式储能优化配置研究[J]. 电测与仪表, 2024, 61(3): 26-32.
FENG J J, ZENG P L, LI Y L, et al. Research on optimal configuration of novel distributed energy storage considering the impact of charging and discharging strategy on energy storage life[J]. Electrical Measurement & Instrumentation, 2024, 61(3): 26-32.
李陇杰, 李蒙恩, 卢勇, 等. 计及寿命损耗及需求响应的储能优化配置方法[J]. 电源学报, 2025, 23(3): 208-219. DOI:10.13234/j.issn.2095-2805.2025.3.208.
LI L J, LI M E, LU Y, et al. Optimal configuration method for energy storage taking into account lifetime losses and demand response[J]. Journal of Power Supply, 2025, 23(3): 208-219. DOI:10.13234/j.issn.2095-2805.2025.3.208.
YU Y, WANG B X, LI M L, et al. Optimized distributed energy management for BESS incorporating time-varying delays with an improved bipartite grouping model simultaneously balancing SOH and SOC[J]. Journal of Energy Storage, 2025, 126: 117006. DOI:10.1016/j.est.2025.117006.
余洋, 李梦璐, 王卜潇, 等. 基于竞争合作机制的电池储能系统分布式功率分配策略[J]. 电工技术学报, 2025, 40(7): 2335-2352. DOI:10.19595/j.cnki.1000-6753.tces.240593.
YU Y, LI M L, WANG B X, et al. A distributed power allocation strategy for battery energy storage systems based on competitive-cooperative mechanism[J]. Transactions of China Electrotechnical Society, 2025, 40(7): 2335-2352. DOI:10.19595/j.cnki.1000-6753.tces.240593.
柳丹, 康逸群, 熊平, 等. 基于深度强化学习的分布式储能聚合控制方法研究[J]. 可再生能源, 2025, 43(9): 1260-1267.
LIU D, KANG Y Q, XIONG P, et al. Research on aggregate control architecture and decision method of multi-point distributed energy storage system[J]. Renewable Energy Resources, 2025, 43(9): 1260-1267.
谭金龙, 陈军, 赵启, 等. 基于改进型双重深度确定性策略梯度与自适应分布式模型预测控制融合的电网侧储能系统协同优化方法[J]. 储能科学与技术, 2025, 14(11): 4289-4299.
TAN J L, CHEN J, ZHAO Q, et al. A grid-side energy storage system optimization method based on improved twin deep deterministic policy gradient and adaptive distributed model predictive control[J]. Energy Storage Science and Technology, 2025, 14(11): 4289-4299.
ZHOU C K, QIAN K J, ALLAN M, et al. Modeling of the cost of EV battery wear due to V2G application in power systems[J]. IEEE Transactions on Energy Conversion, 2011, 26(4): 1041-1050. DOI:10.1109/TEC.2011.2159977.
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