A planning method for the placement and sizing of distributed energy storage system considering the uncertainty of renewable energy sources

doi:10.12028/j.issn.2095-4239.2019.0156

Abstract

Abstract:

Energy storage is characterized by fast response and high flexibility and can provide several auxiliary services for a power grid, which is an important flexible resource that can absorb a considerable proportion of renewable energy. With the rapid decline in energy storage costs, the application of centralized and distributed energy storage in a power grid has recently become the focus of attention of international researchers. This study proposes a two-layer optimization model for the optimal placement and sizing of distributed electrochemical energy storage considering the uncertainty and intermittency associated with the renewable energy output. First, the study establishes an optimal objective function for electrochemical energy storage investment and operating costs considering the renewable energy uncertainty. Second, a two-layer optimization algorithm is applied to solve the sizing and placement of energy storage. The outer layer adopts the branch definition method to determine the energy storage location, whereas the inner layer uses the improved genetic algorithm to obtain the optimal capacity as well as the discharging/charging operation strategy of the storage system. Finally, the proposed method is applied using the IEEE-39 bus test system, and the validity and efficiency of the proposed method are verified.

Key words: renewable energy integration, optimal placement and sizing, two-layer optimization algorithm, distributed energy storage

CLC Number:

TQ 028.8

DING Qian, ZENG Pingliang, SUN Yikai, XU Chenjing, XU Zhenchao. A planning method for the placement and sizing of distributed energy storage system considering the uncertainty of renewable energy sources[J]. Energy Storage Science and Technology, 2020, 9(1): 162-169.

Figures/Tables 10

Fig. 1

Fig.2

Fig.3

Fig.4

Table 1

Table 2

Parameters of the BESS"

编号	性能指标	符号	数值
1	充电效率	$η c$	95%
2	放电效率	$η d$	95%
3	储能电站单位容量成本造价	$p$	2￥m/（MW·h）
4	最大储能电站容量	$C ˉ$	200MW
5	自放电率	$δ$	0.1%
6	最大持续充电功率	$P ˉ i C$	100MW
7	最大持续放电功率	$P ˉ i D$	100MW
8	最小SOC值	$S ? i$	10%
9	最大SOC值	$S ˉ i$	95%
10	初始SOC值	SOC（0）	40%
11	末SOC值	SOC（T）	40%

Table 2

Fig.5

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Fig.7

Fig.8

References 18

1	李凯, 马倩, 徐红兵. 储能系统的荷电状态管理策略及其影响评价[J]. 电力系统自动化, 2015(8): 27-32.
	LI Kai, MA Qian, XU Hongbing. SOC management strategy of storage system and its impact assessment[J]. Automation of Electric Power Systems, 2015(8): 27-32.
2	丁明, 陈忠, 苏建徽. 可再生能源发电中的电池储能系统综述[J]. 电力系统自动化, 2013, 37(1): 19-25.
	DING Ming, CHEN Zhong, SU Jianhui. An overview of battery energy storage system for renewable energy generation[J]. Automation of Electric Power Systems, 2013, 37(1): 19-25.
3	NICK M, CHERKAOUI R, PAOLONE M. Optimal allocation of dispersed energy storage systems in active distribution networks for energy balance and grid support[J]. IEEE Transactions on Power Systems, 2014, 29(5): 2300-2310.
4	李秀磊. 主动配电网中储能和需求侧响应的联合优化规划[J]. 电网技术, 2016, 40(12): 3803-3810.
	LI Xiulei. Integrated optimal planning of energy storage and demand side response in active power distribution network[J]. Power System Technology, 2016, 40(12): 3803-3810.
5	赵金利, 于莹莹, 李鹏. 基于锥优化的储能系统参与配电网运行调节快速计算方法[J]. 电力系统自动化, 2016, 40(2): 30-35.
	ZHAO Jinli, YU Yingying, LI Peng. A fast calculation method of energy storage system for distribution network regulation based on conic programming[J]. Automation of Electric Power Systems, 2016, 40(2): 30-35.
6	马会萌, 李蓓, 李建林. 适用于集中式可再生能源的储容配置敏感因素分析[J]. 电网技术, 2014, 38(2): 328-334.
	MA Huimeng, LI Bei, LI Jianlinn. Analysis on factors sensitive to capacity configuration of battery energy storage system suitable for centralized renewable energy sources[J]. Power System Technology, 2014, 38(2): 328-334.
7	向育鹏, 卫志农, 孙国强. 基于全寿命周期成本的配电网蓄电池储能系统的优化配置[J]. 电网技术, 2015(1): 264-270.
	XIANG Yupeng, WEI Zhinong, SUN Guoqiang. Life cycle cost based optimal configuration of battery energy storage system in distribution network[J]. Power System Technology, 2015(1): 264-270.
8	FERNÁNDEZ-BLANCO RICARDO, DVORKIN Y, XU B, et al. Optimal energy storage siting and sizing: A wecc case study[J]. IEEE Transactions on Sustainable Energy, 2017, 8(2): 733-743.
9	MAKAROV Y V, DU P, KINTNER-MEYER M C W, et al. Sizing energy storage to accommodate high penetration of variable energy resources[J]. IEEE Transactions on Sustainable Energy, 2012, 3(1): 34-40.
10	SOLOMON A A, KAMMEN D M, CALLAWAY D. The role of large-scale energy storage design and dispatch in the power grid: A study of very high grid penetration of variable renewable resources[J]. Applied Energy, 2014, 134: 75-89.
11	BOSE S, GAYME D F, TOPCU U, et al. Optimal placement of energy storage in the grid[C]//Decision & Control, IEEE, 2012.
12	李建林, 马会萌, 袁晓冬. 规模化分布式储能的关键应用技术研究综述[J]. 电网技术, 2017, 41(10): 3365-3375.
	LI Jianlin, MA Huimeng, YUAN Xiaodong. Overview on key applied technologies of large-scale distributed energy storage[J]. Power System Technology, 2017, 41(10): 3365-3375.
13	ATWA Y M, EL-SAADANY E F. Optimal allocation of ess in distribution systems with a high penetration of wind energy[J]. IEEE Transactions on Power Systems, 2010, 25(4): 1815-1822.
14	ZHENG Y, DONG Z Y, LUO F J, et al. Optimal allocation of energy storage system for risk mitigation of DISCOs with high renewable penetrations[J]. IEEE Transactions on Power Systems, 2014, 29(1): 212-220.
15	颜志敏, 王承民, 郑健. 配电网中蓄电池储能系统的价值评估模型[J]. 电力自动化设备, 2013, 33(2): 57-61.
	YAN Zhimin, WANG Chengmin, ZHENG Jian. Value assessment model of battery energy storage system in distribution network[J]. Electic Power Automation Equipment, 2013, 33(2): 57-61.
16	YANG Y, LI H, AICHHORN A, et al. Sizing strategy of distributed battery storage system with high penetration of photovoltaic for voltage regulation and peak load shaving[J]. IEEE Transactions on Smart Grid, 2014, 5(2): 982-991.
17	THOMAS A, SAHA T K, DEEBA S R, et al. Evaluation of technical and financial benefits of battery-based energy storage systems in distribution networks[J]. IET Renewable Power Generation, 2016, 10(8): 1149-1160.
18	RIBEIRO P F, JOHNSON B K, CROW M L, et al. Energy storage systems for advanced power applications[C]//Proceedings of the IEEE, 2001, 89（12）: 1744-1756.

编号	负荷时段	时刻/h	电价/万元·（MW·h）^-1
1	低谷	0—7	0.056
2	平谷	12—16，22—23	0.112
3	高峰	8—11，17—21	0.156

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