考虑储能寿命和经验模态分解的区域配电网混合储能配置

doi:10.19799/j.cnki.2095-4239.2025.0159

摘要/Abstract

摘要：

为了应对区域配电网中新能源发电及负荷功率波动引发的安全稳定问题，同时考虑到新能源发电的高频低频波动耦合以及源荷双侧的波动耦合，本工作提出了一种基于经验模态分解和多目标优化的区域配电网两阶段混合储能配置方法，旨在建立兼顾新能源高低频波动、系统运行经济性与稳定性的协同优化框架。第一阶段模型使用滑动平均滤波器得到混合储能需要平抑的功率波动，然后通过改进的自适应噪声完全集成经验模态分解(improved complete ensemble empirical mode decomposition with adaptive noise，ICEEMDAN)实现并网分钟级波动功率高低频分离，并考虑超级电容综合成本和分钟波动得到最优噪声标准差(noise standard deviation，NSTD)和高低频模态分界数下的超级电容最优配置，以平抑光伏发电分钟级高频波动。第二阶段模型以系统综合成本、网损和电压波动为多目标，基于多目标粒子群算法对混合储能中的电化学储能容量进行优化配置，得到同时满足分钟级和小时级波动的混合储能配置方案，并以IEEE 33节点系统为例验证所提方法的有效性和先进性，结果表明与传统方法相比所提方法能够协同考虑节点高低频波动耦合和系统低频波动耦合，使并网分钟级高频波动量下降91.1%，平均电压偏离量下降10.1%，电压偏差最大值下降55.4%，同时系统网损下降55.9%，系统购电量下降10.88%。

关键词: ICEEMDAN, 混合储能系统, 电压波动, 光伏并网, 两阶段规划

Abstract:

To address the safety and stability issues caused by power fluctuations in renewable energy generation and load in regional distribution networks, while considering the coupling of high- and low-frequency fluctuations on both the generation and load sides, this study proposes a two-stage hybrid energy storage configuration method based on empirical mode decomposition and multi-objective optimization. The framework aims to establish a coordinated optimization mechanism that integrates high-/low-frequency fluctuation mitigation with economic operation and system stability. In the first-stage model, a moving average filter is used to extract the power fluctuations that need to be mitigated by the hybrid energy storage system. The improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is then applied to separate the high- and low-frequency components of the minute-level grid-connected power fluctuations. By considering the comprehensive cost of supercapacitors (SCs) and minute-level fluctuations, the optimal noise standard deviation and the mode boundary number between high- and low-frequency components are determined to achieve an optimal SC configuration for mitigating high-frequency minute-level fluctuations in photovoltaic generation. In the second-stage model, a multi-objective optimization based on an improved multi-objective particle swarm optimization algorithm is conducted to optimize the capacity configuration of the hybrid energy storage system, with the objectives of minimizing the comprehensive system cost, power loss, and voltage fluctuations. This approach provides a configuration scheme that simultaneously addresses minute-level and hourly-level fluctuations. The proposed method is validated using the IEEE 33-node system. The results demonstrate that, compared to traditional methods, this approach effectively considers the coupling of high- and low-frequency fluctuations at individual nodes and across the system. Specifically, it reduces minute-level high-frequency grid-connected fluctuations by 91.1%, the average voltage deviation by 10.1%, the maximum voltage deviation by 55.4%, system power loss by 55.9%, and system purchased electricity by 10.88%.

Key words: ICEEMDAN, hybrid energy storage system, voltage fluctuations, photovoltaic grid integration, two-stage configuration

中图分类号:

TM 732

王凯亮, 孙宇军, 钟锦星, 苏向阳, 李俊辉, 刘宗扬, 蔡煜, 陈艺丹. 考虑储能寿命和经验模态分解的区域配电网混合储能配置[J]. 储能科学与技术, 2025, 14(9): 3417-3430.

Kailiang WANG, Yujun SUN, Jinxing ZHONG, Xiangyang SU, Junhui LI, Zongyang LIU, Yu CAI, Yidan CHEN. Hybrid energy storage configuration for regional distribution network considering energy storage lifespan and empirical mode decomposition[J]. Energy Storage Science and Technology, 2025, 14(9): 3417-3430.

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变量名	取值
ESS单位功率投资成本/(元/kW)	1500
ESS单位容量投资成本/(元/kWh)	1000
SC单位功率投资成本/(元/kW)	1700
SC单位容量投资成本/(元/kWh)	8100
ESS充放电效率	0.9
SC充放电效率	0.95
储能的残值系数	0.9
运维护系数	0.2
系统单位购电成本/(元/kWh)	1.2
系统单位弃电成本/(元/kWh)	2
ESS充放电状态切换损耗成本/(元/次)	0.5
节点9光伏容量/MW	10
节点30光伏容量/MW	10
认知加速度系数范围	[0.1, 0.2]
惯性权重设定在最大值	0.9
惯性权重最小值	0.4
最大迭代次数	100
群体规模	100

方案	原始	M1	M2
SC功率/MW	0	3.555	3.685
SC容量/MWh	0	0.63	2.7
ESS功率/MW	0	0	1.825
ESS容量/MWh	0	0	9.14
安装成本/万元	0	0.244	1.0115
运维成本/万元	0	0.045	0.23
总成本/万元	0	0.268	1.4215
最大功率波动/MW	3.95	0.35	0.2
越限波动占比/%	9	0	0

配置及指标情况	配置前	M1	M2
节点9的SC功率/MW	0	3.555	3.685
节点9的SC容量/MWh	0	0.63	2.7
节点9的ESS功率/MW	0	4.18	1.825
节点9的ESS容量/MWh	0	21.01	9.14
节点30的SC功率/MW	0	3.555	3.685
节点30的SC容量/MWh	0	0.63	2.7
节点30的ESS功率/MW	0	4.42	1.825
节点30的ESS容量/MWh	0	21.31	9.14
综合成本/万元	14.286	19.17	19.925
储能寿命成本/万元	0	3.705	0.795
储能更换次数/次	0	2	1
储能实际寿命/年	—	7.3	10
平均电压/p.u.	0.9573	0.9616	0.9579
电压偏差最大值/p.u.	0.1711	0.0763	0.1640
系统网损/MWh	11.25	4.96	11.05
系统日购电量/MWh	119.03	106.07	118.64
系统日弃电量/MWh	11.46	0	11.93