互联电网控制性能评价标准下储能集群参与AGC控制策略

doi:10.19799/j.cnki.2095-4239.2024.0518

储能科学与技术 ›› 2024, Vol. 13 ›› Issue (11): 4005-4016.doi: 10.19799/j.cnki.2095-4239.2024.0518

互联电网控制性能评价标准下储能集群参与AGC控制策略

郭士琦¹(), 郭东¹, 尚国政², 魏婷婷¹, 郑子萱³(), 陈恩泽³, 李杰³, 张家琛³

^1.国网兴安供电公司，内蒙古乌兰浩特 137400
^2.国网内蒙古东部电力有限公司，内蒙古呼和浩特 010010
^3.四川大学电气工程学院，四川成都 610065

收稿日期:2024-06-11 修回日期:2024-07-15 出版日期:2024-11-28 发布日期:2024-11-27
通讯作者: 郑子萱 E-mail:MDguoshiqi@163.com;scuzzx@163.com
作者简介:郭士琦（1982—），男，硕士，高级工程师，电网调控运行管理，E-mail：MDguoshiqi@163.com；
基金资助:
国网内蒙古东部电力有限公司科技项目(526640230001)

AGC control strategy incorporating energy storage cluster participation under control performance standards for interconnected grids

Shiqi GUO¹(), Dong GUO¹, Guozheng SHANG², Tingting WEI¹, Zixuan ZHENG³(), Enze CHEN³, Jie LI³, Jiachen ZHANG³

^1.Xingan Power Supply Company of State Grid Inner Mongolia East Electric Power Co. , Ltd. , Ulanhot 137400, Inner Mongolia, China
^2.State Grid Inner Mongolia Eastern Power Co. , Ltd. , Hohhot 010010, Inner Mongolia, China
^3.College of Electrical Engineering, Sichuan University, Chengdu 610065, Sichuan, China

Received:2024-06-11 Revised:2024-07-15 Online:2024-11-28 Published:2024-11-27
Contact: Zixuan ZHENG E-mail:MDguoshiqi@163.com;scuzzx@163.com

摘要/Abstract

摘要：

随着储能技术的迅猛发展，利用其快速调节能力缓解自动发电控制（automatic generation control，AGC)过程常规机组的供电压力，对提高系统频率稳定性具有重要意义。然而，在储能协同参与AGC控制过程中，容易出现过充过放、功率分配不合理等问题，导致控制性能标准(control performance standard，CPS)的考核结果不佳。基于此，本文提出一种考虑CPS指标及储能实时运行状态的AGC控制策略。首先，结合AGC控制流程搭建了区域电网调频动态模型，并基于模型各元件响应特性推导了其简化传递函数；其次，为提升功率分配的合理性，先以储能集群的等效荷电状态（state of charge, SOC）为依据，完成储能集群与非储能集群间功率初次分配，再通过对储能SOC的主动管理，考虑实时可调功率的差异性，实现储能集群内部的二次分配；在此基础上，为确保调频指令精确匹配系统调频需求，根据CPS考核反馈结果对控制器参数进行日调整；最后，基于北方某地区实际考核流程和装机规模，以CPS考核结果、频率偏差量以及储能SOC状态等为衡量指标，仿真验证了本文策略在改善CPS考核质量和提升储能调频性能上的可行性和有效性。

关键词: 控制性能标准, 储能集群, 自动发电控制, 功率分配

Abstract:

The rapid advancement of energy storage technologies has enabled the use of their fast regulation capabilities to alleviate power supply pressures on conventional sources during automatic generation control (AGC), enhancing system frequency stability. However, issues such as overcharging, over-discharging, and suboptimal power allocation in energy storage systems during AGC control have led to poor performance evaluations under the control performance standard (CPS). This paper proposes an AGC control strategy that integrates CPS indicators and the real-time state of energy storage. Initially, a dynamic model for frequency regulation is developed based on the AGC control process, and a simplified transfer function is derived according to the response characteristics of each component. To improve the rationality of power allocation, initial distribution between battery energy storage system (BESS) clusters and non-BESS clusters is determined based on the state of charge (SOC), followed by a secondary allocation among individual BESS units considering adjustable power variability. Additionally, controller parameters are fine-tuned using feedback from CPS results to ensure frequency regulation commands align with frequency regulation requirements. Finally, simulations based on actual CPS evaluations, frequency deviations, and the state of energy storage, conducted using data from a northern region's installed capacity, demonstrate that the proposed strategy enhances CPS quality and optimizes the frequency regulation capabilities of energy storage.

Key words: control performance standard, energy storage cluster, automatic generation control, power allocation

中图分类号:

TM 761

郭士琦, 郭东, 尚国政, 魏婷婷, 郑子萱, 陈恩泽, 李杰, 张家琛. 互联电网控制性能评价标准下储能集群参与AGC控制策略[J]. 储能科学与技术, 2024, 13(11): 4005-4016.

Shiqi GUO, Dong GUO, Guozheng SHANG, Tingting WEI, Zixuan ZHENG, Enze CHEN, Jie LI, Jiachen ZHANG. AGC control strategy incorporating energy storage cluster participation under control performance standards for interconnected grids[J]. Energy Storage Science and Technology, 2024, 13(11): 4005-4016.

图/表 20

图1

图2

图3

图4

表1

表2

表3

表4

表5

图5

图6

图7

图8

图9

图10

表6

图11

图12

图13

表7

参考文献 22

1	SIOSHANSI R, DENHOLM P, ARTEAGA J, et al. Energy-storage modeling: State-of-the-art and future research directions[J]. IEEE Transactions on Power Systems, 2022, 37(2): 860-875. DOI: 10.1109/TPWRS.2021.3104768.
2	金力, 房鑫炎, 蔡振华, 等. 考虑特性分布的储能电站接入的电网多时间尺度源储荷协调调度策略[J]. 电网技术, 2020, 44(10): 3641-3650. DOI: 10.13335/j.1000-3673.pst.2020.0330.
	JIN L, FANG X Y, CAI Z H, et al. Multiple time-scales source-storage-load coordination scheduling strategy of grid connected to energy storage power station considering characteristic distribution[J]. Power System Technology, 2020, 44(10): 3641-3650. DOI: 10.13335/j.1000-3673.pst.2020.0330.
3	张超, 康慨, 卢胜, 等. 兼顾储能系统热管理与电池寿命的可再生能源储能电站经济调度[J]. 储能科学与技术, 2021, 10(4): 1353-1363. DOI: 10.19799/j.cnki.2095-4239.2021.0114.
	ZHANG C, KANG K, LU S, et al. Economic scheduling of renewable energy storage plants with integrated thermal management of energy storage systems and battery life[J]. Energy Storage Science and Technology, 2021, 10(4): 1353-1363. DOI: 10.19799/j.cnki.2095-4239.2021.0114.
4	赵霞, 梁钰, 孙名轶, 等. AGC机组动态优化调度模型的凸松弛及其双层迭代算法[J]. 电力系统自动化, 2022, 46(17): 228-238. DOI: 10.7500/AEPS20211012004.
	ZHAO X, LIANG Y, SUN M Y, et al. Convex relaxation and bi-level iterative algorithm for dynamic optimal dispatch model of automatic generation control units[J]. Automation of Electric Power Systems, 2022, 46(17): 228-238. DOI: 10.7500/AEPS 20211012004.
5	汪锋, 刘智强, 张克勇, 等. 基于分时电价与储能充放电策略的台区可调控资源聚合及调度[J]. 储能科学与技术, 2023, 12(4): 1204-1214. DOI: 10.19799/j.cnki.2095-4239.2022.0754.
	WANG F, LIU Z Q, ZHANG K Y, et al. Adjustable resource aggregation and scheduling in distribution transformer station areas based on time-of-use price and charge-discharge strategy of energy storage[J]. Energy Storage Science and Technology, 2023, 12(4): 1204-1214. DOI: 10.19799/j.cnki.2095-4239. 2022. 0754.
6	张荣荣. CPS标准下新能源电力系统AGC机组动态优化调度的改进模型[D]. 重庆: 重庆大学, 2016.ZHANG R R. An improved model for dynamic optimal scheduling of AGC units in new energy power system under CPS standard[D]. Chongqing: Chongqing University, 2016.
7	ZHAO X, YE X B, YANG L, et al. Chance constrained dynamic optimisation method for AGC units dispatch considering uncertainties of the offshore wind farm[J]. The Journal of Engineering, 2019, 2019(16): 2112-2119. DOI: 10.1049/joe. 2018.8558.
8	赵霞, 叶晓斌, 杨仑, 等. CPS标准下AGC机组动态优化调度的改进方法[J]. 电力系统及其自动化学报, 2019, 31(10): 31-36, 44. DOI: 10.19635/j.cnki.csu-epsa.000172.
	ZHAO X, YE X B, YANG L, et al. Improved method for dynamic optimal dispatch of AGC units under CPS[J]. Proceedings of the CSU-EPSA, 2019, 31(10): 31-36, 44. DOI: 10.19635/j.cnki.csu-epsa.000172.
9	孙乐平, 韩帅, 吴宛潞, 等. 基于经济模型预测控制的多虚拟电厂两阶段协调优化调度[J]. 储能科学与技术, 2021, 10(5): 1845-1853. DOI: 10.19799/j.cnki.2095-4239.2021.0195.
	SUN L P, HAN S, WU W L, et al. Coordinated optimal scheduling of multiple virtual power plants in multiple time scales based on economic model predictive control[J]. Energy Storage Science and Technology, 2021, 10(5): 1845-1853. DOI: 10.19799/j.cnki. 2095-4239.2021.0195.
10	姜涛, 邱宇琛, 刘先超, 等. 多风电场支撑电网频率稳定的动态差异化时序协同控制策略[J]. 电力系统自动化, 2024, 48(8): 162-173.
	JIANG T, QIU Y C, LIU X C, et al. Control strategy with dynamic and differentiated timing synergy for multiple wind farms supporting frequency stability of power grid[J]. Automation of Electric Power Systems, 2024, 48(8): 162-173.
11	韩健民, 薛飞宇, 梁双印, 等. 模糊控制优化下的混合储能系统辅助燃煤机组调频仿真[J]. 储能科学与技术, 2022, 11(7): 2188-2196. DOI: 10.19799/j.cnki.2095-4239.2021.0664.
	HAN J M, XUE F Y, LIANG S Y, et al. Hybrid energy storage system assisted frequency modulation simulation of the coal-fired unit under fuzzy control optimization[J]. Energy Storage Science and Technology, 2022, 11(7): 2188-2196. DOI: 10.19799/j.cnki.2095-4239.2021.0664.
12	叶林, 陈超宇, 张慈杭, 等. 基于分布式模型预测控制的风电场参与AGC控制方法[J]. 电网技术, 2019, 43(9): 3261-3270. DOI: 10.13335/j.1000-3673.pst.2019.0205.
	YE L, CHEN C Y, ZHANG C H, et al. Wind farm participating in AGC based on distributed model predictive control[J]. Power System Technology, 2019, 43(9): 3261-3270. DOI: 10.13335/j.1000-3673.pst.2019.0205.
13	曹钰, 姜彤, 刘炽, 等. 考虑频率特性及储能电池状态的电化学储能参与一次调频控制策略[J]. 储能科学与技术, 2023, 12(10): 3120-3130. DOI: 10.19799/j.cnki.2095-4239.2023.0281.
	CAO Y, JIANG T, LIU C, et al. Electrochemical energy storage participation in primary frequency regulation control strategy considering frequency characteristics and energy storage battery state[J]. Energy Storage Science and Technology, 2023, 12(10): 3120-3130. DOI: 10.19799/j.cnki.2095-4239.2023.0281.
14	CHOI J Y, CHOI I S, AHN G H, et al. Advanced power sharing method to improve the energy efficiency of multiple battery energy storages system[J]. IEEE Transactions on Smart Grid, 2018, 9(2): 1292-1300. DOI: 10.1109/TSG.2016.2582842.
15	吴罗兰. 计及多维度频率控制性能评价标准的最优频率控制策略研究[D]. 宜昌: 三峡大学, 2020. DOI: 10.27270/d.cnki.gsxau. 2020. 000634.
	WU L L. Research on optimal frequency control strategy considering multi-dimensional frequency control performance evaluation criteria[D]. Yichang: China Three Gorges University, 2020. DOI: 10.27270/d.cnki.gsxau.2020.000634.
16	宋学杰. 基于CPS标准的区域电网自动发电控制性能考核优化方案研究[D]. 上海: 上海交通大学, 2015.SONG X J. Research on optimization scheme of automatic generation control performance assessment in regional power grid based on CPS standard[D]. Shanghai: Shanghai Jiao Tong University, 2015.
17	刘莹. 电化学储能电站参与电力系统二次调频功率分配策略[D]. 吉林: 东北电力大学, 2021.LIU Y. Power distribution strategy of electrochemical energy storage power station participating in secondary frequency modulation of power system[D]. Jilin: Northeast Dianli University, 2021.
18	张圣祺, 刘何毓, 汪飞, 等. 面向电网二次调频需求的"PXP" 储能集群分布式均衡控制策略[J]. 中国电机工程学报, 2022, 42(3): 886-900. DOI: 10.13334/j.0258-8013.pcsee.210531.
	ZHANG S Q, LIU H Y, WANG F, et al. A balancing control strategy for "power-X-power" energy storage cluster in system load frequency control[J]. Proceedings of the CSEE, 2022, 42(3): 886-900. DOI: 10.13334/j.0258-8013.pcsee.210531.
19	于昌海, 庞腊成, 吴继平, 等. 计及多点电池储能系统的电网二次调频协同控制[J]. 电力工程技术, 2024, 43(1): 68-76. DOI: 10.12158/j.2096-3203.2024.01.008.
	YU C H, PANG L C, WU J P, et al. Coordination control for secondary frequency regulation with participation of multiple battery energy storage systems[J]. Electric Power Engineering Technology, 2024, 43(1): 68-76. DOI: 10.12158/j.2096-3203. 2024.01.008.
20	焦盘龙. 储能辅助火电机组二次调频控制策略及容量优化配置研究[D]. 吉林: 东北电力大学, 2020. DOI: 10.27008/d.cnki.gdbdc. 2020.000096.
	JIAO P L. Study on secondary frequency modulation control strategy and optimal capacity allocation of energy storage auxiliary thermal power units[D]. Jilin: Northeast Dianli University, 2020. DOI: 10.27008/d.cnki.gdbdc.2020.000096.
21	张圣祺, 袁蓓, 徐青山, 等. 规模化储能参与下的电网二次调频优化控制策略[J]. 电力自动化设备, 2019, 39(5): 82-88, 95. DOI: 10.16081/j.issn.1006-6047.2019.05.012.
	ZHANG S Q, YUAN B, XU Q S, et al. Optimal control strategy of secondary frequency regulation for power grid with large-scale energy storages[J]. Electric Power Automation Equipment, 2019, 39(5): 82-88, 95. DOI: 10.16081/j.issn.1006-6047.2019.05.012.
22	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.

考核区间	指标要求	罚款计算原则	奖励计算原则
A（优）	CPS1>200%	不罚款	总罚款金额的60%
B（良）	100%>CPS1>200%&CPS2合格	0.03 AVG_15min(ACE)×(2-CPS1)	总罚款金额的30%
C（中）	100%>CPS1>200%&CPS2不合格	0.03 AVG_15min(ACE)×(2-CPS1)	总罚款金额的10%
D（差）	CPS1<100%	0.15 AVG_15min(ACE)×(2-CPS1)	不奖励

所属时段	时间段	罚款单价(元/kWh)
高峰段	05：00—07：00，10：00—12：00，16：00—20：00	0.15(B、C区)，0.75(D区)
低谷段	02：00—04：00	0.06(B、C区)，0.3(D区)
平时段	其余时段	0.03(B、C区)，0.15(D区)

储能编号	额定功率 /MW	额定容量 /MWh	充电效率	放电效率	基准荷电状态
储能1	40	40	0.9	0.95	0.5
储能2	30	20	0.9	0.8	0.5
储能3	20	5	0.95	0.9	0.5

场景	\|Δf\|均值/Hz	\|Δf\|最大值/Hz	CPS1/%	\|ACE\|均值/MW	\|P_arrb\|均值/MW	等效SOC
场景1	0.04543	0.16703	163.9	0.8999	—	—
场景2	0.04532	0.19035	157.1	0.8845	1.1480	0.315
场景3	0.04252	0.15017	167.0	0.7652	0.0163	0.368
场景4	0.04057	0.14806	167.7	0.7478	0.0037	0.361

场景	CPS合格率/%	日结算罚款额/元	AGC总输出功率指令均值/MW
场景1	57.26	4526.75	4.669
场景2	65.37	6962.98	5.414
场景3	71.85	3877.49	5.248
场景4	90.95	2051.28	4.644

互联电网控制性能评价标准下储能集群参与AGC控制策略

AGC control strategy incorporating energy storage cluster participation under control performance standards for interconnected grids

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 20

参考文献 22

相关文章 6

编辑推荐

Metrics

本文评价

[1]	郭东泽, 张继红, 王庆宇, 张帅. 平抑风电出力波动的混合储能功率分配策略[J]. 储能科学与技术, 2024, 13(5): 1564-1573.
[2]	宋元明, 刘亚杰, 金光, 周星, 黄旭程. 锂离子电池/超级电容器混合储能系统能量管理方法综述[J]. 储能科学与技术, 2024, 13(2): 652-668.
[3]	曹钰, 姜彤, 刘炽, 杨勇, 刘文飞, 刘文颖. 考虑频率特性及储能电池状态的电化学储能参与一次调频控制策略[J]. 储能科学与技术, 2023, 12(10): 3120-3130.
[4]	章宝歌, 李萍, 张振, 王宇, 荣耀. 应用于城轨列车混合储能系统的能量管理策略[J]. 储能科学与技术, 2020, 9(1): 204-210.
[5]	李瑞民, 张新敬, 徐玉杰, 孙雯雯, 周学志, 郭丛, 陈海生. 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.
[6]	米根锁, 穆艳停. 一种适用于光伏并网混合储能系统的功率分配策略[J]. 储能科学与技术, 2018, 7(4): 726-731.