考虑资源相关性的新能源场站群集中式共享储能优化配置

孙英聪, 陈来军, 李笑竹, 梅生伟

太阳能学报 ›› 2024, Vol. 45 ›› Issue (7) : 2-9.

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (7) : 2-9. DOI: 10.19912/j.0254-0096.tynxb.2023-2083
“新型电力系统中光储规划配置及优化运行技术”专题

考虑资源相关性的新能源场站群集中式共享储能优化配置

  • 孙英聪1, 陈来军1,2, 李笑竹1, 梅生伟1,2
作者信息 +

OPTIMAL ALLOCATION OF CENTRALIZED SHARED ENERGY STORAGE FOR RENEWABLE ENERGY STATION CLUSTERS WITH CONSIDERATION OF RESOURCE CORRELATION

  • Sun Yingcong1, Chen Laijun1,2, Li Xiaozhu1, Mei Shengwei1,2
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文章历史 +

摘要

针对区域内新能源场站群联合出力场景的集中式共享储能配置规划问题,提出考虑资源相关性,即风光出力互补特性、各新能源场站出力空间相关性的新能源场站群共享储能优化配置策略。该策略首先利用Copula方法进行典型场景生成,以剖析风光资源的相关性与互补性;在此基础上,建立新能源场站群集中式共享储能的优化配置模型,以实现多主体间储能的共享与互补利用,同时尽可能利用风光资源的相关性。最后通过仿真分析验证所提方法的正确性和有效性。

Abstract

An optimal allocation strategy for shared energy storage systems in a cluster of renewable energy stations is proposed, which considers the complementary characteristics of wind and solar energy and the spatial correlation of the power output of each renewable energy station. The strategy first uses Copula method to generate typical scenarios to analyze the correlation and complementarity of the renewable resources, then establishes an optimal allocation model for centralized shared energy storage systems in the cluster of renewable energy stations to realize the sharing and complementary use of energy storage among multiple entities, while exploiting the correlation and complementarity of wind and solar resources as far as possible. Finally, the correctness and effectiveness of the proposed method are verified by simulation analysis.

关键词

新能源 / 储能 / 相关性方法 / 风光互补特性 / 空间相关性

Key words

new energy / energy storage / correlation methods / complementary characteristics of wind and solar / spatial correlation

引用本文

导出引用
孙英聪, 陈来军, 李笑竹, 梅生伟. 考虑资源相关性的新能源场站群集中式共享储能优化配置[J]. 太阳能学报. 2024, 45(7): 2-9 https://doi.org/10.19912/j.0254-0096.tynxb.2023-2083
Sun Yingcong, Chen Laijun, Li Xiaozhu, Mei Shengwei. OPTIMAL ALLOCATION OF CENTRALIZED SHARED ENERGY STORAGE FOR RENEWABLE ENERGY STATION CLUSTERS WITH CONSIDERATION OF RESOURCE CORRELATION[J]. Acta Energiae Solaris Sinica. 2024, 45(7): 2-9 https://doi.org/10.19912/j.0254-0096.tynxb.2023-2083
中图分类号: TM614   

参考文献

[1] 孟高军, 张峰, 徐晓轶, 等. 基于网络安全稳定约束的新能源消纳能力评估方法[J]. 太阳能学报, 2023, 44(11): 505-512.
MENG G J, ZHANG F, XU X Y, et al.New energy consumption capacity assessment method based on network securityand stability constraints[J]. Acta energiae solaris sinica, 2023, 44(11): 505-512.
[2] 田博文, 张志禹. 基于多目标合作博弈的储能平滑风功率运行控制策略[J]. 高电压技术, 2023, 49(6): 2546-2557.
TIAN B W, ZHANG Z Y.Control strategy of energy storage smooth wind power operation based on multi-objective cooperative game[J]. High voltage engineering, 2023, 49(6): 2546-2557.
[3] DAI R, ESMAEILBEIGI R, CHARKHGARD H.The utilization of shared energy storage in energy systems: a comprehensive review[J]. IEEE transactions on smart grid, 2021, 12(4): 3163-3174.
[4] 闫东翔, 陈玥. 共享储能商业模式和定价机制研究综述[J]. 电力系统自动化, 2022, 46(23): 178-191.
YAN D X, CHEN Y.Review on business model and pricing mechanism for shared energy storage[J]. Automation of electric power systems, 2022, 46(23): 178-191.
[5] 马昱欣, 胡泽春, 刁锐. 新能源场站共享储能提供调频服务的日前优化策略[J]. 电网技术, 2022, 46(10): 3857-3868.
MA Y X, HU Z C, DIAO R.Day-ahead optimization strategy for shared energy storage of renewable energy power stations to provide frequency regulation service[J]. Power system technology, 2022, 46(10): 3857-3868.
[6] 孙偲, 陈来军, 邱欣杰, 等. 基于合作博弈的发电侧共享储能规划模型[J]. 全球能源互联网, 2019, 2(4): 360-366.
SUN C, CHEN L J, QIU X J, et al.A generation-side shared energy storage planning model based on cooperative game[J]. Journal of global energy interconnection, 2019, 2(4): 360-366.
[7] 何锦华, 吴斌, 曹敏健, 等. 面向辅助服务的新能源场站共享储能容量优化配置[J]. 电力工程技术, 2022, 41(6): 50-57.
HE J H, WU B, CAO M J, et al.Capacity optimization configuration of shared energy storage in renewable energy stations for ancillary service[J]. Electric power engineering technology, 2022, 41(6): 50-57.
[8] 王再闯, 陈来军, 李笑竹, 等. 基于合作博弈的产销者社区分布式光伏与共享储能容量优化[J]. 电工技术学报, 2022, 37(23): 5922-5932.
WANG Z C, CHEN L J, LI X Z, et al.Capacity optimization of distributed PV and shared energy storage of prosumer community based on cooperative game[J]. Transactions of China Electrotechnical Society, 2022, 37(23): 5922-5932.
[9] MA M T, HUANG H J, SONG X L, et al.Optimal sizing and operations of shared energy storage systems in distribution networks: a bi-level programming approach[J]. Applied energy, 2022, 307: 118170.
[10] 杜锡力, 李笑竹, 陈来军, 等. 面向多场景调节需求的集中式共享储能鲁棒优化配置[J]. 电工技术学报, 2022, 37(23): 5911-5921.
DU X L, LI X Z, CHEN L J, et al.Robust and optimized configuration of centralized shared energy storage for multi-scenario regulation demand[J]. Transactions of China Electrotechnical Society, 2022, 37(23): 5911-5921.
[11] 简川黔, 刘继春, 蒲天骄, 等. 共建共享模式下考虑需求响应的多售电主体风光储容量优化方法[J]. 电力自动化设备, 2021, 41(9): 206-214.
JIAN C Q, LIU J C, PU T J, et al.Wind-photovoltaic-storage capacity optimization method for multiple electricity sell entities considering demand response under co-construction and sharing mode[J]. Electric power automation equipment, 2021, 41(9): 206-214.
[12] 张晓英, 张艺, 王琨, 等. 基于改进NSGA-Ⅱ算法的含分布式电源配电网无功优化[J]. 电力系统保护与控制, 2020, 48(1): 55-64.
ZHANG X Y, ZHANG Y, WANG K, et al.Reactive power optimization of distribution network with distributed generations based on improved NSGA-Ⅱ algorithm[J]. Power system protection and control, 2020, 48(1): 55-64.
[13] 王玲玲, 王昕, 郑益慧, 等. 计及多个风电机组出力相关性的配电网无功优化[J]. 电网技术, 2017, 41(11): 3463-3469.
WANG L L, WANG X, ZHENG Y H, et al.Reactive power optimization of distribution network considering output correlation of multiple wind turbines[J]. Power system technology, 2017, 41(11): 3463-3469.
[14] 孙媛媛, 程凯强, 许庆燊, 等. 考虑光伏出力相关性的主动配电网薄弱环节识别[J]. 电力系统自动化, 2022, 46(15): 96-103.
SUN Y Y, CHENG K Q, XU Q S, et al.Identification of weak link for active distribution network considering correlation of photovoltaic output[J]. Automation of electric power systems, 2022, 46(15): 96-103.
[15] WANG Q, ZHANG X G, YI C Z, et al.A novel shared energy storage planning method considering the correlation of renewable uncertainties on the supply side[J]. IEEE transactions on sustainable energy, 2022, 13(4): 2051-2063.
[16] 李军, 胡非, 王丙兰, 等. 风速的Weibull分布参数[J]. 太阳能学报, 2012, 33(10): 1667-1671.
LI J, HU F, WANG B L, et al.Weibull parameters for wind speed[J]. Acta energiae solaris sinica, 2012, 33(10): 1667-1671.
[17] 侯亚丽, 栗广浩, 杨宇昕, 等. 基于现场测量的建筑环境风场特征分析及风力机出力评估[J]. 太阳能学报, 2023, 44(11): 318-324.
HOU Y L, LI G H, YANG Y X, et al.Wind energy potential and micro-wind turbine performance analysis based on site measure ments in urban environment[J]. Acta energiae solaris sinica, 2023, 44(11): 318-324.
[18] 魏勇, 李浩然, 范雪峰, 等. 计及日照强度时间周期特征的光伏并网系统风险评估方法[J]. 电网技术, 2018, 42(8): 2562-2569.
WEI Y, LI H R, FAN X F, et al.Risk assessment method of PV integrated power system considering time periodic characteristics of solar irradiance[J]. Power system technology, 2018, 42(8): 2562-2569.
[19] 谢敏, 熊靖, 刘明波, 等. 基于Copula的多风电场出力相关性建模及其在电网经济调度中的应用[J]. 电网技术, 2016, 40(4): 1100-1106.
XIE M, XIONG J, LIU M B, et al.Modeling of multi wind farm output correlation based on Copula and its application in power system economic dispatch[J]. Power system technology, 2016, 40(4): 1100-1106.
[20] 韩子娇, 李正文, 张文达, 等. 计及光伏出力不确定性的氢能综合能源系统经济运行策略[J]. 电力自动化设备, 2021, 41(10): 99-106.
HAN Z J, LI Z W, ZHANG W D, et al.Economic operation strategy of hydrogen integrated energy system considering uncertainty of photovoltaic output power[J]. Electric power automation equipment, 2021, 41(10): 99-106.
[21] 江岳文, 郑晨昕. 风电场群联合共享储能两阶段协同并网优化[J]. 电网技术, 2022, 46(9): 3426-3439.
JIANG Y W, ZHENG C X.Two-stage operation optimization for grid-connected wind farm cluster with shared energy storage[J]. Power system technology, 2022, 46(9): 3426-3439.
[22] 陆秋瑜, 罗澍忻, 胡伟, 等. 集群风储联合系统广域协调控制及利益分配策略[J]. 电力系统自动化, 2019, 43(20): 183-191.
LU Q Y, LUO S X, HU W, et al.Wide-area coordinated control and benefit assignment strategy of clustering wind-energy storage integrated system[J]. Automation of electric power systems, 2019, 43(20): 183-191.
[23] 国家能源局南方监管局.南方区域风电并网运行及辅助服务管理实施细则[EB/OL].(2022-06-13)[2024-05-17]. https://nfj.nea.gov.cn/hdhy/zlxz/202402/t20240208_244591.html
Southern Regulatory Bureau of the National Energy Administration. Implementation rules for grid-connected operation and auxiliary service management of wind power in the southern region[EB/OL].(2022-06-13)[2024-05-17]. https://nfj.nea.gov.cn/hdhy/zlxz/202402/t20240208_244591.html

基金

国家自然科学基金联合基金项目(U22A20224); 国家自然科学基金面上项目(52077109)

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