
1. 国网新疆电力有限公司经济技术研究院, 新疆维吾尔自治区,乌鲁木齐市,830011
2. 新疆大学 电气工程学院,新疆维吾尔自治区,乌鲁木齐市,830047
Published:2026
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SONG Haiming, YU Zhongping, GUAN Honghao, et al. Coordinated Operation Strategy for Energy Storage in New Energy Collection System for Power Generation Plan Tracking and Peak Shaving[J]. 2026, 43(2): 368-379.
SONG Haiming, YU Zhongping, GUAN Honghao, et al. Coordinated Operation Strategy for Energy Storage in New Energy Collection System for Power Generation Plan Tracking and Peak Shaving[J]. 2026, 43(2): 368-379. DOI: 10.19725/j.cnki.1007-2322.2023.0395.
针对新能源汇集区域多储能系统在单一应用场景下储能利用率不高、汇集系统整体经济性较差的问题,考虑新能源跟踪计划误差分布特性和汇集区域电网净负荷峰谷特性,让储能协助新能源跟踪发电计划的同时辅助系统调峰。根据新能源出力特性和负荷功率特征,将储能运行区域划分为调峰区、跟踪计划区及荷电状态(states of charge,SOC)优化区,并提出一种面向发电计划跟踪与调峰的汇集系统储能分区协调优化运行策略。考虑新能源调峰成本分摊,跟踪计划误差惩罚,储能循环寿命成本、储能充放电转换成本等因素,针对不同区域分别建立储能优化运行模型。构建汇集系统整体跟踪计划出力效果评价指标、储能辅助系统调峰评价指标以及储能系统SOC评价指标,针对汇集系统优化运行结果进行评价。仿真结果表明,所提策略可以有效提升新能源跟踪计划出力能力,缓解系统调峰压力,降低新能源汇集系统整体运行成本,保证储能后续动作的可持续性。
In response to the issues of low energy storage utilization rate and poor overall economic efficiency of multiple energy storage systems in a single application scenario in the new energy gathering area
the peak valley characteristics of the net load of the power grid as well as the error distribution characteristics of the new energy tracking plan are taken into account. In this context
energy storage can assist the system in peak shaving while aligning with the power generation plan. The energy storage operation area is divided into peak shaving area
tracking planning area and states of charge (SOC) optimization area based on the output characteristics and load power characteristics of the new energy. A coordinated and optimized operation strategy for energy storage zones in a centralized system is proposed for power generation plan tracking and peak shaving. Then
considering the factors such as new energy peak shaving cost allocation
tracking plan error penalty
energy storage cycle life cost
and energy storage charging and discharging conversion cost
the energy storage optimization operation models for different regions are established respectively
Indicators for overall tracking plan output effect evaluation of the collection system
peak shaving evaluation of the energy storage auxiliary system
as well as SOC evaluation of the energy storage system
are provided. Additionally
the optimization operation results of the collection system are assessed. The simulation results demonstrate that the proposed strategy can effectively enhance the output capacity of the new energy tracking plan
alleviate the peak shaving pressure of the system
reduce the overall operating cost of the new energy collection system
and ensure the sustainability of subsequent energy storage actions.
LI Haobo, ZOU Hairong, ZHU Jianhong. Fuzzy control system for energy storagescheduling considering wind power plan tracking[J]. Power System Protection and Control, 2021, 49(01): 125−132(in Chinese).
LI Bin, DENG Youxiong, CHEN Biyun. Advanced rolling optimization control strategy of wind storage system with ultra-short-term wind power prediction enhancement treatment[J]. Power System Technology, 2021, 45(06): 2280−2287(in Chinese).
TELEKE S, BARAN M E, BHATTACHARYA S, et al . Optimal control of battery energy storage for wind farm dispatching[J ] . IEEE Transactions on Energy Conversion, 2010, 25(3): 787−794.
LI Q, CHOI S S, YUAN Y, et al . On the determination of battery energy storage capacity and short-term power dispatch of a wind farm[J ] . IEEE Transactions on Sustainable Energy, 2011, 2(2): 148−158.
YAN G G, ZHENG X D, MU G, et al . A quasiautomated generation control strategy for multiple energy storage systems to optimize low-carbon benefits[J ] . Journal of Modern Power Systems and Clean Energy, 2015, 3(1): 93−102.
LI Junhui, ZHANG Jiahui, LI Cuiping, et al . Configuration scheme and economic analysis of energy storage system participating in peak shaving[J ] . Transactions of China Electrotechnical Society, 2021, 36(19): 4148−4160(in Chinese).
CHENG Yu, CHEN Xi. Analysis of the influence of energy storage on wind power absorption capacity based on source-load-storage interaction[J]. Automation of Electric Power Systems, 2022, 46(13): 84−93(in Chinese).
LI Junhui, AN Chenyu, LI Cuiping, et al . Multi-objective optimization scheduling method of energy storage, new energy and thermal power considering peak shaving market transaction[J ] . Transactions of China Electrotechnical Society, 2023, 38(23): 6391−6406(in Chinese).
SIGRIST L, LOBATO E, ROUCO L. Energy storage systems providing primary reserve and peak shaving in small isolated power systems: An economic assessment[J]. International Journal of Electrical Power Energy Systems, 2013, 53: 675−683.
LEVRON Y, SHMILOVITZ D. Power systems’ optimal peak-shaving applying secondary storage[J]. Electric Power Systems Research, 2012, 89: 80−84.
CHEN Changqing, LI Xinran, ZHANG Bingyu, et al . Cooperative control strategy of energy storage peak regulation and frequency modulation based on multi-time scale[J ] . Power System Protection and Control, 2022, 50(05): 94−105(in Chinese).
WANG Xueyan. Research on energy storage multi-scenario application control method based on scene feature analysis[D]. Changsha: Hunan University, 2020(in Chinese).
CAO Jiarui. Wind storage System participating in multi-application scenario collaborative optimization Strategy [D]. Taiyuan: Taiyuan University of Technology, 2022(in Chinese).
KARGARIAN A, HUG G, MOHAMMADI J. A multi-time scale co-optimization method for sizing of energy storage and fast-ramping generation[J]. IEEE Transactions on Sustainable Energy, 2016, 7(4): 1351−1361.
XUE Yushi, XU Shaohua, LI Jianlin, et al . Research on cooperative operation and switching strategy of Multiple working modes of photovoltaic power station energy storage system[J ] . Electrical Appliances and Energy Efficiency Management Technology, 2017(13): 46−55(in Chinese).
LU Qiuyu, HU Wei, MIN Yong, et al . A multi-pattern coordinated optimization strategy of wind power and energy storage system considering temporal dependence[J ] . Automation of Electric Power Systems, 2015, 39(2): 6−12(in Chinese).
LU Qiuyu, LUO Shuxin, HU Wei, et al . Multi-mode coordination optimization strategy of wind storage system considering time correlation[J ] . Automation of Electric Power Systems, 2019, 43(20): 183−191(in Chinese).
DONG Yaguang, LI Fengting, WANG Sen. Energy storage coordinated operation strategy of new energy station and gathering station for tracking planned output[J]. Power System Technology, 2023, 47(04): 1579−1591(in Chinese).
YANG Libin, CAO Yang, WEI Wei, et al . Wind farm energy storage capacity allocation method considering wind power uncertainty and curtailment rate constraints[J ] . Automation of Electric Power Systems, 2020, 44(16): 45−52(in Chinese).
LI Junhui, HOU Tao, YAN Gangui, et al . Frequency modulation power bi-level optimization of multiple energy storage system considering frequency modulation cost and state of charge recovery[J ] . Proceedings of the CSEE, 2021, 41(23): 8020−8033(in Chinese).
ZHAO Shuqiang, WU Yang, LI Zhiwei, et al . Peak shiller capacity and economic analysis of power system considering uncertainty of wind and solar output[J ] . Power System Technology, 2022, 46(05): 1752−1761(in Chinese).
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