Allocation method of operational efficiency of multi-shared energy storages in the distribution network based on improved-Shapley value

doi:10.19799/j.cnki.2095-4239.2024.0888

Abstract

Abstract:

The configuration of multiple shared energy storages (SESs) in a new distribution network (NDN) has become a trend, providing multi-resource cooperative effects. However, maximizing the efficiency of SESs requires more than just evaluating their value. The multifaceted and comprehensive impacts of each SES on the NDN must also be considered. To quantify the marginal operational contribution of a single SES under the joint effect of multiple SESs in the NDN, a method for allocating the operational efficiency of multi-SESs based on the improved Shapley value method is proposed. An optimized scheduling model was established to minimize operating costs in the NDN while considering new energy consumption and carbon emission reduction. The model includes operational efficiency evaluation indicators that evaluate the economic, reliability, and environmental impacts of SESs on the NDN. In addition, an operational efficiency evaluation model is established on the basis of a subjective-objective empowerment method, combining improved hierarchical analysis and inter-criteria correlation. To consider the differences in the unilateral efficiency of different SESs, correction factors were introduced to improve the Shapley value method. These factors consider each SES's economic, reliability, and environmental contributions to allocate operational efficiencies across multiple SES combinations. The proposed method was validated via simulations on an improved IEEE 33-node NDN with three SESs. The results demonstrate that the proposed method effectively quantifies and allocates the comprehensive utility of SESs at different nodes using the NDN. In particular, the operational efficiency of SES1 and SES2, which positively affect the NDN, is increased. The proposed method provides a new framework for the efficient scheduling and potential utilization of SESs in distribution networks.

Key words: shared energy storage, efficiency evaluation, efficiency allocation, Shapley value, carbon emission reduction

CLC Number:

TK 02

Junbo HAO, Xiaohong YAN, Honglan PEI, Wenqiang ZHANG, Chun XIAO. Allocation method of operational efficiency of multi-shared energy storages in the distribution network based on improved-Shapley value[J]. Energy Storage Science and Technology, 2025, 14(4): 1507-1518.

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References 19

1	刘佳婕, 贾燕冰, 韩肖清, 等. 基于效能评估的混合储能电站调频功率优化[J]. 高电压技术, 2024, 50(6): 2467-2477. DOI: 10.13336/j.1003-6520.hve.20222027.
	LIU J J, JIA Y B, HAN X Q, et al. Frequency modulation power optimization of hybrid energy storage power station based on efficiency evaluation[J]. High voltage engineering, 2024, 50(6): 2467-2477. DOI: 10.13336/j.1003-6520.hve.20222027.
2	陈海生, 李泓, 徐玉杰, 等. 2023年中国储能技术研究进展[J]. 储能科学与技术, 2024, 13(5): 1359-1397.
	CHEN H S, LI H, XU Y J, et al. Research progress of energy storage technology in China in 2023[J]. Energy Storage Science and Technology, 2024, 13(5): 1359-1397.
3	唐西胜, 李伟, 沈晓东. 面向新型电力系统的储能规划方法研究进展及展望[J]. 电力系统自动化, 2024, 48(9): 178-191.
	TANG X S, LI W, SHEN X D. Research progress and prospect of energy storage planning method for new power system[J]. Automation of Electric Power Systems, 2024, 48(9): 178-191.
4	刘阳, 滕卫军, 谷青发, 等. 规模化多元电化学储能度电成本及其经济性分析[J]. 储能科学与技术, 2023, 12(1): 312-318. DOI: 10.19799/j.cnki.2095-4239.2022.0348.
	LIU Y, TENG W J, GU Q F, et al. Scaled-up diversified electrochemical energy storage LCOE and its economic analysis[J]. Energy Storage Science and Technology, 2023, 12(1): 312-318. DOI: 10.19799/j.cnki.2095-4239.2022.0348.
5	朱文韬, 周杨, 徐艺敏, 等. 电池储能技术在新能源发电系统中的应用与优化[J]. 储能科学与技术, 2024, 13(8): 2737-2739. DOI: 10.19799/j.cnki.2095-4239.2024.0690.
	ZHU W T, ZHOU Y, XU Y M, et al. Application and optimization of battery energy storage technology in new energy generation system[J]. Energy Storage Science and Technology, 2024, 13(8): 2737-2739. DOI: 10.19799/j.cnki.2095-4239.2024.0690.
6	李明, 郑云平, 亚夏尔·吐尔洪, 等. 新型储能政策分析与建议[J]. 储能科学与技术, 2023, 12(6): 2022-2031. DOI: 10.19799/j.cnki.2095-4239.2023.0140.
	LI M, ZHENG Y P, ARTHUR Turhoun, et al. Analysis and suggestions on new energy storage policy[J]. Energy Storage Science and Technology, 2023, 12(6): 2022-2031. DOI: 10.19799/j.cnki.2095-4239.2023.0140.
7	李朝晖, 谷青发, 刘阳, 等. 计及经济性最优的共享储能选型评估方法[J/OL]. 高压电器, 2023: 1-10. (2023-12-21). https://kns.cnki.net/KCMS/detail/detail.aspx?filename=GYDQ20231220003&dbname=CJFD&dbcode=CJFQ.
	LI Z H, GU Q F, LIU Y, et al. Evaluation method of shared energy storage selection considering optimal economy[J/OL]. China Industrial Economics, 2023: 1-10. (2023-12-21). https://kns.cnki.net/KCMS/detail/detail.aspx?filename=GYDQ20231220003&dbname=CJFD&dbcode=CJFQ.
8	黄山河. 用户侧共享储能协同交易定价机制与综合效益评估方法研究[D]. 长沙: 湖南大学, 2023.
9	张哲, 林胤, 陈子轩, 等. 用户侧共享式储能的全寿命周期经济效益评估[J]. 浙江电力, 2023, 42(3): 47-54. DOI: 10.19585/j.zjdl. 202303006.
	ZHANG Z, LIN Y, CHEN Z X, et al. Life cycle economic benefit evaluation based on user-side shared energy storage[J]. Zhejiang Electric Power, 2023, 42(3): 47-54. DOI: 10.19585/j.zjdl.202303006.
10	叶鹏, 刘思奇, 关多娇, 等. 基于自适应均衡技术的分布式储能聚合模型及评估方法[J]. 上海交通大学学报, 2021, 55(12): 1689-1699. DOI: 10.16183/j.cnki.jsjtu.2021.322.
	YE P, LIU S Q, GUAN D J, et al. An aggregation model and evaluation method of distributed energy storage based on adaptive equalization technology[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1689-1 699. DOI: 10.16183/j.cnki.jsjtu.2021.322.
11	屈克庆, 乔敬茂, 毛玲, 等. 共享储能电站优化配置及选址评价方法[J/OL]. 现代电力: 1-9[2024-07-01].
	QU K Q, QIAO J M, MAO L, et al. Optimal configuration and site-selection evaluation method for shared energy storage stations[J/OL]. Modern Electric Power:1-9[2024-07-01].
12	王蓓蓓, 胡维涵, 牟玉亭, 等. 储能对高比例新能源电力系统的容量价值贡献及机制思考[J]. 电网技术, 2024, 48(6): 2520-2531. DOI: 10.13335/j.1000-3673.pst.2023.2076.
	WANG B B, HU W H, MOU Y T, et al. Contribution of energy storage to capacity value of high proportion new energy power system and its mechanism thinking[J]. Power System Technology, 2024, 48(6): 2520-2531. DOI: 10.13335/j.1000-3673.pst.2023.2076.
13	孙伟卿, 罗静, 张婕. 高比例风电接入的电力系统储能容量配置及影响因素分析[J]. 电力系统保护与控制, 2021, 49(15): 9-18. DOI: 10.19783/j.cnki.pspc.201322.
	SUN W Q, LUO J, ZHANG J. Energy storage capacity allocation and influence factor analysis of a power system with a high proportion of wind power[J]. Power System Protection and Control, 2021, 49(15): 9-18. DOI: 10.19783/j.cnki.pspc.201322.
14	SHAPLEY L S. A value for n-persons games[J]. Annals of Mathematics Studies,1953, 28: 307-318.
15	刘寅韬, 江全元, 耿光超, 等. 基于合作联盟的电化学储能共享模式研究[J]. 电网技术, 2024, 48(5): 1947-1956. DOI: 10.13335/j.1000-3673.pst.2023.0552.
	LIU Y T, JIANG Q Y, GENG G C, et al. Sharing model of electrochemical energy storage based on cooperative alliance[J]. Power System Technology, 2024, 48(5): 1947-1956. DOI: 10.13335/j.1000-3673.pst.2023.0552.
16	田欣, 陈来军, 李笑竹, 等. 基于主从博弈和改进Shapley值的分布式光伏社区共享储能优化运行策略[J]. 电网技术, 2023, 47(6): 2252-2261. DOI: 10.13335/j.1000-3673.pst.2022.1814.
	TIAN X, CHEN L J, LI X Z, et al. Optimal scheduling for energy storage sharing among communities with photovoltaic resource based on stackelberg game and improved Shapley value[J]. Power System Technology, 2023, 47(6): 2252-2261. DOI: 10.13335/j.1000-3673.pst.2022.1814.
17	段佳南, 谢俊, 赵心怡, 等. 基于改进Shapley值法的风-光-水-储多主体互补发电系统合作增益分配策略[J]. 电力自动化设备, 2024, 44(3): 22-30.
	DUAN J N, XIE J, ZHAO X Y, et al. Cooperative synergistic benefit allocation strategy of wind-solar-hydro-energy storage multi-stakeholder complementary generation system based on improved Shapley value method[J]. Electric Power Automation Equipment, 2024,44(03):22-30.
18	崔杨, 周慧娟, 仲悟之, 等. 考虑源荷两侧不确定性的含风电电力系统低碳调度[J]. 电力自动化设备, 2020, 40(11): 85-93.
	CUI Y, ZHOU H J,ZHONG W Z, et al. Lowcarbon scheduling of power system with wind power considering uncertainty of both source and load sides[J]. Electric Power Automation Equipment, 2020, 40(11): 85-93.
19	VENKATESH B, RANJAN R, GOOI H B. Optimal reconfiguration of radial distribution systems to maximize loadability[J]. IEEE Transactions on Power Systems, 2004, 19(1): 260-266. DOI: 10.1109/TPWRS.2003.818739.

共享储能	功率限值/kW	容量/kWh	荷电状态	充放电效率
SES1	800	4800	0.20~0.85	0.90
SES2	600	3600	0.30~0.95	0.95
SES3	400	2400	0.20~0.90	0.85

指标	主观权重	客观权重	综合权重
B1	0.2706	0.1353	0.2256
B2	0.1879	0.2668	0.3089
B3	0.0725	0.2213	0.0988
B4	0.0870	0.1304	0.0699
B5	0.2255	0.1398	0.1942
B6	0.1565	0.1064	0.1026

序号	共享储能运行组合	运行效能值
1	SES1	0.2706
2	SES2	0.1547
3	SES3	0.1638
4	SES1、SES2	0.8794
5	SES1、SES3	0.4097
6	SES2、SES3	0.4230
7	SES1、SES2、SES3	0.9860

共享储能	经济贡献度	可靠性贡献度	环境贡献度
SES1	0.4184	0.4397	0.4848
SES2	0.3780	0.4772	0.3479
SES3	0.2036	-0.0097	0.1672

共享储能	策略1		策略2		策略3
共享储能	运行效能	占比/%	运行效能	占比/%	运行效能	占比/%
SES1	0.3566	36.17	0.4396	44.59	0.5431	55.09
SES2	0.3104	31.48	0.3883	39.38	0.4410	44.73
SES3	0.3190	32.35	0.1580	16.03	0.0018	0.18