Research on capacity optimization configuration and operation strategy of energy storage system considering wind and solar consumption

doi:10.19799/j.cnki.2095-4239.2024.0165

Abstract

Abstract:

Under the background of dual carbon, the comprehensive consideration of energy storage system capacity allocation method and operation strategy can help to improve the rate of wind and solar renewable energy consumption and guarantee the economic and safe operation of the system. In the planning stage of the energy storage system, this paper proposes an optimization configuration strategy for the energy storage system that takes into account operating costs for different wind-landscape collaborative consumption scenarios. Firstly, an objective function is established to minimize operating costs, including wind and light abandonment, as well as energy storage investment costs. Secondly, all system constraints are considered. Finally, the energy storage capacity is planned for different scenarios to reduce wind and solar abandonment and increase renewable energy absorption. During the energy storage system's operation stage, a double-layer operation strategy is proposed to address the poor state of charge (SOC) balance and implementation difficulties. In the upper layer, the optimal battery subsystem for charging and discharging is selected based on the SOC and charging/discharging capacity of the energy storage battery subsystem. In the lower layer, power is optimized with the goal of achieving SOC balance for the battery unit. Based on the AOE control configuration, the strategy is implemented by creating a configuration file using Excel. It has the advantages of low difficulty of use, simple writing, intuitive control process, high calculation and operation efficiency, which is of great significance for slowing down the aging of the battery, reducing the difficulty of realizing the operation strategy of the user, and effectively consuming the wind-scenery renewable energy.

Key words: energy storage system, capacity optimization allocation, operation strategy, SOC balance, AOE

CLC Number:

TM 912

Zhanwei LI, Dongfang FAN, Chao ZENG, Wenqian HE, Jin HE. Research on capacity optimization configuration and operation strategy of energy storage system considering wind and solar consumption[J]. Energy Storage Science and Technology, 2024, 13(8): 2713-2725.

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References 25

1	邓婷婷, 娄素华, 田旭, 等. 计及需求响应与火电深度调峰的含风电系统优化调度[J]. 电力系统自动化, 2019, 43(15): 34-41. DOI: 10.7500/AEPS20180602005.
	DENG T T, LOU S H, TIAN X, et al. Optimal dispatch of power system integrated with wind power considering demand response and deep peak regulation of thermal power units[J]. Automation of Electric Power Systems, 2019, 43(15): 34-41. DOI: 10.7500/AEPS20180602005.
2	李翠萍, 卓君武, 李军徽, 等. 光伏发电与风光联合发电系统输出特性分析[J]. 电网与清洁能源, 2017, 33(1): 95-102. DOI: 10.3969/j.issn.1674-3814.2017.01.015.
	LI C P, ZHUO J W, LI J H, et al. Characteristic analysis of photovoltaic power generation and wind-photovoltaic joint power generation system[J]. Power System and Clean Energy, 2017, 33(1): 95-102. DOI: 10.3969/j.issn.1674-3814.2017.01.015.
3	袁小明. 大规模风电并网问题基本框架[J]. 电力科学与技术学报, 2012, 27(1): 16-18. DOI: 10.3969/j.issn.1673-9140.2012.01.004.
	YUAN X M. Framework of problems in large scale wind integration[J]. Journal of Electric Power Science and Technology, 2012, 27(1): 16-18. DOI: 10.3969/j.issn.1673-9140.2012.01.004.
4	吴雄, 王秀丽, 李骏, 等. 风电储能混合系统的联合调度模型及求解[J]. 中国电机工程学报, 2013, 33(13): 10-17. DOI: 10.13334/j.0258-8013.pcsee.2013.13.008.
	WU X, WANG X L, LI J, et al. A joint operation model and solution for hybrid wind energy storage systems[J]. Proceedings of the CSEE, 2013, 33(13): 10-17. DOI: 10.13334/j.0258-8013.pcsee.2013.13.008.
5	谢毓广, 江晓东. 储能系统对含风电的机组组合问题影响分析[J]. 电力系统自动化, 2011, 35(5): 19-24.
	XIE Y G, JIANG Xiaodong. Impact of energy storage system on the unit commitment problem with volatile wind power[J]. Automation of Electric Power Systems, 2011, 35(5): 19-24.
6	GARCIA-GONZALEZ J, DE LA MUELA R M R, SANTOS L M, et al. Stochastic joint optimization of wind generation and pumped-storage units in an electricity market[J]. IEEE Transactions on Power Systems, 2008, 23(2): 460-468. DOI: 10.1109/TPWRS.2008.919430.
7	刘畅, 卓建坤, 赵东明, 等. 利用储能系统实现可再生能源微电网灵活安全运行的研究综述[J]. 中国电机工程学报, 2020, 40(1): 1-18, 369. DOI: 10.13334/j.0258-8013.pcsee.190212.
	LIU C, ZHUO J K, ZHAO D M, et al. A review on the utilization of energy storage system for the flexible and safe operation of renewable energy microgrids[J]. Proceedings of the CSEE, 2020, 40(1): 1-18, 369. DOI: 10.13334/j.0258-8013.pcsee.190212.
8	周楠, 樊玮, 刘念, 等. 基于需求响应的光伏微网储能系统多目标容量优化配置[J]. 电网技术, 2016, 40(6): 1709-1716. DOI: 10.13335/j.1000-3673.pst.2016.06.015.
	ZHOU N, FAN W, LIU N, et al. Battery storage multi-objective optimization for capacity configuration of PV-based microgrid considering demand response[J]. Power System Technology, 2016, 40(6): 1709-1716. DOI: 10.13335/j.1000-3673.pst.2016.06.015.
9	李瑞民, 张新敬, 徐玉杰, 等. 风光互补系统中混合储能容量优化配置研究[J]. 储能科学与技术, 2019, 8(3): 512-522. DOI: 10.12028/j.issn.2095-4239.2019.0014.
	LI R M, ZHANG X J, XU Y J, et al. Research on optimal configuration of hybrid energy storage capacity for wind-solar generation system[J]. Energy Storage Science and Technology, 2019, 8(3): 512-522. DOI: 10.12028/j.issn.2095-4239.2019.0014.
10	OGIMI K, YOZA A, YONA A, et al. A study on optimum capacity of battery energy storage system for wind farm operation with wind power forecast data[C]//2012 IEEE 15th International Conference on Harmonics and Quality of Power. Hong Kong, China. IEEE, 2012: 118-123. DOI: 10.1109/ICHQP.2012.6381230.
11	朱兰, 严正, 杨秀, 等. 风光储微网系统蓄电池容量优化配置方法研究[J]. 电网技术, 2012, 36(12): 26-31. DOI: 10.13335/j.1000-3673.pst.2012.12.021.
	ZHU L, YAN Z, YANG X, et al. Optimal configuration of battery capacity in microgrid composed of wind power and photovoltaic generation with energy storage[J]. Power System Technology, 2012, 36(12): 26-31. DOI: 10.13335/j.1000-3673.pst.2012.12.021.
12	史昭娣, 朱宁, 李政, 等. 基于分解协调的风光储联合规划分层优化方法[J]. 电力工程技术, 2023, 42(6): 22-31. DOI: 10.12158/j.2096-3203.2023.06.003.
	SHI Z D, ZHU N, LI Z, et al. Joint planning and hierarchical optimization method of wind photovoltaic storage based on decomposition coordination[J]. Electric Power Engineering Technology, 2023, 42(6): 22-31. DOI: 10.12158/j.2096-3203.2023.06.003.
13	金辰晖, 姜新建, 戴兴建. 微电网飞轮储能阵列协调控制策略研究[J]. 储能科学与技术, 2018, 7(5): 834-840. DOI: 10.12028/j.issn.2095-4239.2018.0115.
	JIN C H, JIANG X J, DAI X J. Coordinated control strategy of flywheel energy storage array for micro-grid[J]. Energy Storage Science and Technology, 2018, 7(5): 834-840. DOI: 10.12028/j.issn.2095-4239.2018.0115.
14	王磊, 杜晓强, 宋永端. 用于风电场的飞轮储能矩阵系统协调控制[J]. 电网技术, 2013, 37(12): 3406-3412. DOI: 10.13335/j.1000-3673.pst.2013.12.024.
	WANG L, DU X Q, SONG Y D. Coordinated control of flywheel energy storage matrix system for wind farm[J]. Power System Technology, 2013, 37(12): 3406-3412. DOI: 10.13335/j.1000-3673.pst.2013.12.024.
15	李辉, 付博, 杨超, 等. 多级钒电池储能系统的功率优化分配及控制策略[J]. 中国电机工程学报, 2013, 33(16): 70-77, 16. DOI: 10.13334/j.0258-8013.pcsee.2013.16.016.
	LI H, FU B, YANG C, et al. Power optimization distribution and control strategies of multistage vanadium redox flow battery energy storage systems[J]. Proceedings of the CSEE, 2013, 33(16): 70-77, 16. DOI: 10.13334/j.0258-8013.pcsee.2013.16.016.
16	孙纯军, 倪春花, 窦晓波. 基于 SOC 状态反馈的混合储能功率优化策略[J]. 电测与仪表, 2016, 53(15): 81-88. DOI: 10.3969/j.issn.1001-1390.2016.15.016.
	SUN C J, NI C H, DOU X B. Research on optimal power allocation strategy based on SOC state feedback in hybrid energy storage system[J]. Electrical Measurement & Instrumentation, 2016, 53(15): 81-88. DOI: 10.3969/j.issn.1001-1390.2016.15.016.
17	蔡新雷, 董锴, 孟子杰, 等. 基于优化动态分组技术的电池储能电站跟踪AGC指令控制策略[J]. 储能科学与技术, 2022, 11(5): 1475-1481. DOI: 10.19799/j.cnki.2095-4239.2021.0619.
	CAI X L, DONG K, MENG Z J, et al. AGC command tracking control strategy for battery energy storage power station based on optimized dynamic grouping technology[J]. Energy Storage Science and Technology, 2022, 11(5): 1475-1481. DOI: 10.19799/j.cnki.2095-4239.2021.0619.
18	陈薇, 狄那, 邱亚, 等. VRB储能系统多目标优化功率分配策略[J]. 高电压技术, 2020, 46(5): 1518-1527. DOI: 10.13336/j.1003-6520.hve.20200515006.
	CHEN W, DI N, QIU Y, et al. Power distribution strategy based on multi-objective optimization of vanadium redox battery energy storage systems[J]. High Voltage Engineering, 2020, 46(5): 1518-1527. DOI: 10.13336/j.1003-6520.hve.20200515006.
19	张学, 裴玮, 梅春晓, 等. 含电/氢复合储能系统的孤岛直流微电网模糊功率分配策略与协调控制方法[J]. 高电压技术, 2022, 48(3): 958-968. DOI: 10.13336/j.1003-6520.hve.20210283.
	ZHANG X, PEI W, MEI C X, et al. Fuzzy power allocation strategy and coordinated control method of islanding DC microgrid with electricity/hydrogen hybrid energy storage systems[J]. High Voltage Engineering, 2022, 48(3): 958-968. DOI: 10.13336/j.1003-6520.hve.20210283.
20	刘平, 李树胜, 李光军, 等. 基于磁悬浮储能飞轮阵列的地铁直流电能循环利用系统及实验研究[J]. 储能科学与技术, 2020, 9(3): 910-917. DOI: 10.19799/j.cnki.2095-4239.2020.0096.
	LIU P, LI S S, LI G J, et al. Experimental research on DC power recycling system in the subway based on the magnetically suspended energy-storaged flywheel array[J]. Energy Storage Science and Technology, 2020, 9(3): 910-917. DOI: 10.19799/j.cnki.2095-4239.2020.0096.
21	邱亚, 李鑫, 陈薇, 等. 基于P-AWPSO算法的全钒液流电池储能系统功率分配[J]. 高电压技术, 2020, 46(2): 500-510. DOI: 10.13336/j.1003-6520.hve.20200131014.
	QIU Y, LI X, CHEN W, et al. Power distribution of vanadium redox battery energy storage system based on P-AWPSO algorithm[J]. High Voltage Engineering, 2020, 46(2): 500-510. DOI: 10.13336/j.1003-6520.hve.20200131014.
22	FAISAL M, HANNAN M A, KER P J, et al. Fuzzy-based charging-discharging controller for lithium-ion battery in microgrid applications[J]. IEEE Transactions on Industry Applications, 2021, 57(4): 4187-4195. DOI: 10.1109/TIA.2021.3072875.
23	王睿琪, 薛熙臻, 黄阮明, 等. 面向新能源波动平抑的储能多参数等价折算配置方法[J]. 电网技术, 2024, 48(4): 1498-1510. DOI: 10.13335/j.1000-3673.pst.2023.1597.
	WANG R Q, XUE X Z, HUANG R M, et al. Multi-parameter equivalent conversion configuration method for energy storage with new energy fluctuation smoothing[J]. Power System Technology, 2024, 48(4): 1498-1510. DOI: 10.13335/j.1000-3673.pst.2023.1597.
24	董树锋, 刘灵冲, 唐坤杰, 等. 基于Simulink和低代码控制器的储能控制实验教学方法[J]. 储能科学与技术, 2022, 11(7): 2386-2397. DOI: 10.19799/j.cnki.2095-4239.2021.0723.
	DONG S F, LIU L C, TANG K J, et al. The teaching method of energy storage control experiment based on Simulink and low-code controller[J]. Energy Storage Science and Technology, 2022, 11(7): 2386-2397. DOI: 10.19799/j.cnki.2095-4239.2021.0723.
25	GONZÁLEZ I, CALDERÓN A J, PORTALO J M. Innovative multi-layered architecture for heterogeneous automation and monitoring systems: Application case of a photovoltaic smart microgrid[J]. Sustainability, 2021, 13(4): 2234. DOI: 10.3390/su13042234.

编号	走廊	电抗/p.u.	容量/MW	已有数目	编号	走廊	电抗/p.u.	容量/MW	已有数目
1	1-2	0.40	100	1	9	2-6	0.30	100	3
2	1-3	0.38	100	0	10	3-4	0.59	82	0
3	1-4	0.60	80	1	11	3-5	0.20	100	2
4	1-5	0.20	100	1	12	3-6	0.48	100	0
5	1-6	0.68	70	0	13	4-5	0.63	75	0
6	2-3	0.20	100	2	14	4-6	0.30	100	0
7	2-4	0.40	100	1	15	5-6	0.61	78	0
8	2-5	0.31	100	0

发电厂节点	最小出力/MW	最大出力/MW	爬坡率/(MW/h)
1	81.675	181.5	18.15
3	269.775	599.5	59.95
6	24.750	55.0	5.50

负荷节点	最大负荷/MW	负荷节点	最大负荷/MW
1	80	4	160
2	120	5	240
3	40	6	0

时间/h	1	2	3	4	5	6	7	8
负荷/MW	0.867	0.843	0.815	0.789	0.762	0.748	0.753	0.763
光伏出力/MV	0	0	0	0	0.1	0.15	0.2	0.25
风电出力/MV	1.000	0.923	0.887	0.906	0.813	0.691	0.651	0.538

时间/h	9	10	11	12	13	14	15	16
负荷/MW	0.795	0.894	0.951	0.996	0.977	0.973	1.000	0.986
光伏出力/MV	0.5	0.7	0.9	0.9	0.95	0.95	0.9	0.7
风电出力/MV	0.437	0.340	0.285	0.239	0.230	0.285	0.314	0.418

时间/h	17	18	19	20	21	22	23	24
负荷/MW	0.985	0.980	0.936	0.914	0.933	0.944	0.955	0.933
光伏出力/MV	0.5	0.3	0.1	0	0	0	0	0
风电出力/MV	0.553	0.613	0.650	0.846	0.756	0.747	0.667	0.601

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