考虑碳效益和运行策略的风电场储能优化配置

刘道兵; 李珏岑; 齐越; 郭营营; 鲍妙生

doi:10.19912/j.0254-0096.tynxb.2023-1565

PDF(2155 KB)

太阳能学报 ›› 2025, Vol. 46 ›› Issue (2) : 664-675. DOI: 10.19912/j.0254-0096.tynxb.2023-1565

考虑碳效益和运行策略的风电场储能优化配置

刘道兵, 李珏岑, 齐越, 郭营营, 鲍妙生

作者信息 +

WIND FARM ENERGY STORAGE OPTIMIZATION CONFIGNRATION CONSIDERING CARBON BENEFIT AND OPERATION STRATEGY

Liu Daobing, Li Juecen, Qi Yue, Guo Yingying, Bao Miaosheng

Author information +

文章历史 +

摘要

中国碳交易及辅助服务市场的逐步开放丰富了新能源电站储能的收益模式,提出一种考虑碳效益和运行策略的风电场储能优化配置方法。首先,构建储能综合效益计算模型,考虑储能增发电量效益、调频效益、碳效益和全寿命成本;其次,为协调储能同时参与风电平抑和辅助调频,建立储能运行-配置双层模型。上层模型以储能出力最小和充放能力最大为目标,采用模型算法控制求解平抑作用域,兼顾可充放电能力确定调频作用域。基于作用域制定考虑荷电状态（SOC）的多场景协调运行策略。下层储能优化配置模型以综合效益最大为目标,上层求解结果和运行策略为约束,采用哈里斯鹰算法求解。最后,通过算例验证了所提风电场储能优化配置方法有效性。

Abstract

The gradual opening of China’s carbon emissions trading and auxiliary services market has enriched the revenue model of energy storage in new energy power stations. A wind farm energy storage optimization allocation method considering carbon benefit and operation strategy is proposed in this paper. Firstly, a comprehensive benefit calculation model for energy storage is constructed, which takes into account the energy storage incremental capacity benefit, frequency regulation benefit, carbon benefit and whole life cost. Secondly, in order to coordinate energy storage to participate in wind power smoothing and auxiliary frequency regulation at the same time, a two-layer model of energy storage operation-configuration is established. The upper layer model aims to minimize the energy storage output and maximize the charging and discharging capacity, and adopts the model algorithm to control and solve the smoothing scope, and takes into account the charging and discharging capacity to determine the frequency regulation scope. A multi-scenario coordinated operation strategy considering SOC is developed based on the role scopes. The lower layer model is solved by the Harris Hawk algorithm with the objective of maximizing the integrated benefits, and the upper layer solution results and operation strategies as constraints. Finally, the article verifies the effectiveness of the proposed method for

导出引用

刘道兵, 李珏岑, 齐越, 郭营营, 鲍妙生. 考虑碳效益和运行策略的风电场储能优化配置[J]. 太阳能学报. 2025, 46(2): 664-675 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1565

Liu Daobing, Li Juecen, Qi Yue, Guo Yingying, Bao Miaosheng. WIND FARM ENERGY STORAGE OPTIMIZATION CONFIGNRATION CONSIDERING CARBON BENEFIT AND OPERATION STRATEGY[J]. Acta Energiae Solaris Sinica. 2025, 46(2): 664-675 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1565

中图分类号： TM614

参考文献

[1] 吕萍, 石耀鹏. 中国风电产业进入市场化高质量发展阶段[J]. 风能, 2023(5): 72-76.
LYU P, SHI Y P.China wind power industry has entered the stage of market-oriented and high-quality development[J]. Wind energy, 2023(5): 72-76.
[2] 张智刚, 康重庆. 碳中和目标下构建新型电力系统的挑战与展望[J]. 中国电机工程学报, 2022, 42(8): 2806-2819.
ZHANG Z G, KANG C Q.Challenges and prospects for constructing the new-type power system towards a carbon neutrality future[J]. Proceedings of the CSEE, 2022, 42(8): 2806-2819.
[3] 周博, 艾小猛, 方家琨, 等. 计及超分辨率风电出力不确定性的连续时间鲁棒机组组合[J]. 电工技术学报, 2021, 36(7): 1456-1467.
ZHOU B, AI X M, FANG J K, et al.Continuous-time modeling based robust unit commitment considering beyond-the-resolution wind power uncertainty[J]. Transactions of China Electrotechnical Society, 2021, 36(7): 1456-1467.
[4] 杨立滨, 曹阳, 魏韡, 等. 计及风电不确定性和弃风率约束的风电场储能容量配置方法[J]. 电力系统自动化, 2020, 44(16): 45-52.
YANG L B, CAO Y, WEI W, et al.Configuration method of energy storage for wind farms considering wind power uncertainty and wind curtailment constraint[J]. Automation of electric power systems, 2020, 44(16): 45-52.
[5] LIN L, JIA Y Q, MA M H, et al.Long-term stable operation control method of dual-battery energy storage system for smoothing wind power fluctuations[J]. International journal of electrical power & energy systems, 2021, 129: 106878.
[6] 吴智泉, 贾纯超, 陈磊, 等. 新型电力系统中储能创新方向研究[J]. 太阳能学报, 2021, 42(10): 444-451.
WU Z Q, JIA C C, CHEN L, et al.Research on innovative direction of energy storage in new power system construction[J]. Acta energiae solaris sinica, 2021, 42(10): 444-451.
[7] 许高秀, 王旭, 邓晖, 等. 考虑调频需求及风光出力不确定性的储能系统参与能量-调频市场运行策略[J]. 电网技术, 2023, 47(6): 2317-2330.
XU G X, WANG X, DENG H, et al.Optimal operation strategy of energy storage system’s participation in energy and regulation market considering uncertainties of regulation requirements and wind-photovoltaic output[J]. Power system technology, 2023, 47(6): 2317-2330.
[8] 齐先军, 郑夕炜, 王晓蓉, 等. 基于时频分析的改进小波包风电功率波动平抑方法[J]. 太阳能学报, 2022, 43(7): 302-309.
QI X J, ZHENG X W, WANG X R, et al.Improved wavelet packet method of smoothing wind power fluctuations based on time-frequency analysis[J]. Acta energiae solaris sinica, 2022, 43(7): 302-309.
[9] 齐晓光, 姚福星, 朱天曈, 等. 考虑大规模风电接入的电力系统混合储能容量优化配置[J]. 电力自动化设备, 2021, 41(10): 11-19.
QI X G, YAO F X, ZHU T T, et al.Capacity optimization configuration of hybrid energy storage in power system considering large-scale wind power integration[J]. Electric power automation equipment, 2021, 41(10): 11-19.
[10] 汤杰, 李欣然, 黄际元, 等. 以净效益最大为目标的储能电池参与二次调频的容量配置方法[J]. 电工技术学报, 2019, 34(5): 963-972.
TANG J, LI X R, HUANG J Y, et al.Capacity allocation of BESS in secondary frequency regulation with the goal of maximum net benefit[J]. Transactions of China Electrotechnical Society, 2019, 34(5): 963-972.
[11] 马兰, 谢丽蓉, 叶林, 等. 基于混合储能双层规划模型的风电波动平抑策略[J]. 电网技术, 2022, 46(3): 1016-1029.
MA L, XIE L R, YE L, et al.Wind power fluctuation suppression strategy based on hybrid energy storage Bi-level programming model[J]. Power system technology, 2022, 46(3): 1016-1029.
[12] 王明, 李欣然, 谭绍杰, 等. 考虑经济性的风储联合双应用的储容配置方法[J]. 电力系统及其自动化学报, 2017, 29(2): 7-13.
WANG M, LI X R, TAN S J, et al.Capacity configuration method of energy storage in wind-ESS coordination considering economic efficiency[J]. Proceedings of the Csu-Epsa, 2017, 29(2): 7-13.
[13] 李军徽, 侯涛, 穆钢, 等. 电力市场环境下考虑风电调度和调频极限的储能优化控制[J]. 电工技术学报, 2021, 36(9): 1791-1804.
LI J H, HOU T, MU G, et al.Optimal control strategy for energy storage considering wind farm scheduling plan and modulation frequency limitation under electricity market environment[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1791-1804.
[14] YI T, YE H D, LI Q X, et al.Energy storage capacity optimization of wind-energy storage hybrid power plant based on dynamic control strategy[J]. Journal of energy storage, 2022, 55: 105372.
[15] 袁世琦, 潘鹏程, 魏业文, 等. 园区综合能源系统低碳经济优化调度模型研究[J]. 太阳能学报, 2024, 45(3): 347-356.
YUAN S Q, PAN P C, WEI Y W, et al.Study on low-carbon economic optimal scheduling model of community integrated energy system[J]. Acta energiae solaris sinica, 2024, 45(3): 347-356.
[16] 陈崇德, 郭强, 宋子秋, 等. 计及碳收益的风电场混合储能容量优化配置[J]. 中国电力, 2022, 55(12): 22-33.
CHEN C D, GUO Q, SONG Z Q, et al.Optimal configuration of hybrid energy storage capacity for wind farms considering carbon trading revenue[J]. Electric power, 2022, 55(12): 22-33.
[17] 郝婷, 樊小朝, 王维庆, 等. 阶梯式碳交易下考虑源荷不确定性的储能优化配置[J]. 电力系统保护与控制, 2023, 51(1): 101-112.
HAO T, FAN X C, WANG W Q, et al.Optimal configuration of energy storage considering the source-load uncertainty under ladder-type carbon trading[J]. Power system protection and control, 2023, 51(1): 101-112.
[18] 罗凤章, 米肇丰, 王成山, 等. 并网光伏发电工程的低碳综合效益分析模型[J]. 电力系统自动化, 2014, 38(17): 163-169.
LUO F Z, MI Z F, WANG C S, et al.Comprehensive low-carbon benefit analysis models of grid-connected photovoltaic power generation projects[J]. Automation of electric power systems, 2014, 38(17): 163-169.
[19] 中华人民共和国生态环境部. 2019年度减排项目中国区域电网基准线排放因子[EB/OL]. [2022-04-08].Ministry of Ecology and Environment of the People’s Republic of China. Emission reduction projects for the 2019 China regional power grid baseline emission factors[EB/OL]. https://www.mee.gov.cn/ywgz/ydqhbh/wsqtkz/202012/W020201229610353816665.pdf
[20] 宋元明, 刘亚杰, 金光, 等. 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.
SONG Y M, LIU Y J, JIN G, et al.Review of energy management methods for lithium-ion battery/supercapacitor hybrid energy storage systems[J]. Energy storage science and technology, 2024, 13(2): 652-668.
[21] 刘军, 甘乾煜, 张泽秋, 等. 考虑储能电池运行寿命的风电功率波动平抑方法研究[J]. 电网技术, 2023, 47(5): 2098-2108.
LIU J, GAN Q Y, ZHANG Z Q, et al.Research on wind power fluctuation suppression method considering the operating life of energy storage battery[J]. Power system technology, 2023, 47(5): 2098-2108.
[22] 刘颖明, 王晓东, 彭朝阳. 计及储能出力水平的平滑风电功率模型预测控制策略[J]. 电网技术, 2020, 44(5): 1723-1731.
LIU Y M, WANG X D, PENG C Y.Model predictive control strategy for smoothing wind power with energy storage output level[J]. Power system technology, 2020, 44(5): 1723-1731.
[23] HEIDARI A A, MIRJALILI S, FARIS H, et al.Harris Hawks optimization: algorithm and applications[J]. Future generation computer systems, 2019, 97: 849-872.
[24] PJM. RTO Regulation Signal Data[DB/OL]. (2021-7-2)[2022-04-28]. https://www.pjm.com/-/media/markets-ops/ancillary/regulation-signal-posting.ashx.
[25] 国家市场监督管理总局, 国家标准化管理委员会. 风电场接入电力系统技术规定第1部分: 陆上风电: GB/T 19963.1—2021[S]. 北京: 中国标准出版社, 2021.
Standardization Administration of the People's Republic of China. Technical specification for connecting wind farm to power system—Part 1: On shore wind power: GB/T 19963.1—2021[S]. Beijing: Standards Press of China, 2021.