THREE-LAYER CAPACITY CONFIGURATION METHOD FOR MULTI-SCENARIO WIND-THERMAL-HYDROGEN-STORAGE SYSTEM BASED ON AHP-BCO-GRA

Han Xiaojuan; Yang Xiaoyan; Li Haoyu; Guo Siqi

doi:10.19912/j.0254-0096.tynxb.2024-1261

PDF(3962 KB)

Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (11) : 509-520. DOI: 10.19912/j.0254-0096.tynxb.2024-1261

THREE-LAYER CAPACITY CONFIGURATION METHOD FOR MULTI-SCENARIO WIND-THERMAL-HYDROGEN-STORAGE SYSTEM BASED ON AHP-BCO-GRA

Han Xiaojuan, Yang Xiaoyan, Li Haoyu, Guo Siqi

Author information +

History +

Abstract

This paper proposes a three-layer capacity optimization configuration method for multi scenario wind-thermal-hydrogen-storage multi energy complementary systems based on analytic hierarchy process （AHP）-border collie optimization （BCO）-grey relationship analysis （GRA） to address the issues of grid fluctuations and insufficient peak shaving capacity caused by a high proportion of new energy grid integration. The improved complementary ensemble empirical mode decomposition with adaptive noise （ICEEMDAN） technique is utilized to decompose wind power output and optimize the adaptive capacity distribution among lithium iron phosphate batteries, alkaline electrolyzers, and proton exchange membrane electrolyzers. Taking into account the economic, environmental and reliability of thermal power units, the optimal capacity of thermal power units is determined using AHP for smoothing wind power fluctuations and deep peak shaving scenarios; An optimal capacity configuration model for energy storage systems is established using BCO with the goal of minimizing the cost of multi-energy complementary systems. From the perspective of safety in the electric hydrogen coupling system, GRA is used to verify the rationality of the capacity configuration results of the electric hydrogen coupling system. The effectiveness of this method is verified through actual operating data from a power station in China. The simulation results show that the grid connected fluctuation rate of 10 minutes obtained by the method proposed in this paper is the lowest at 15.58%, and the deep peak shaving depth of the auxiliary thermal power unit decreases from 30% to 24.99%.

Key words

multi-energy complementary system / electricity-hydrogen coupled energy storage / three-layer optimization / multiple application scenarios / capacity configuration

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Han Xiaojuan, Yang Xiaoyan, Li Haoyu, Guo Siqi. THREE-LAYER CAPACITY CONFIGURATION METHOD FOR MULTI-SCENARIO WIND-THERMAL-HYDROGEN-STORAGE SYSTEM BASED ON AHP-BCO-GRA[J]. Acta Energiae Solaris Sinica. 2025, 46(11): 509-520 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1261

References

[1] ZHANG J T, CHENG C T, YU S, et al.Preliminary feasibility analysis for remaking the function of cascade hydropower stations to enhance hydropower flexibility: A case study in China[J]. Energy, 2022, 260: 125163.
[2] 舒印彪, 赵勇, 赵良, 等. “双碳” 目标下我国能源电力低碳转型路径[J]. 中国电机工程学报, 2023, 43(5): 1663-1671.
SHU Y B, ZHAO Y, ZHAO L, et al.Study on low carbon energy transition path toward carbon peak and carbon neutrality[J]. Proceedings of the CSEE, 2023, 43(5): 1663-1671.
[3] 国家能源局. 曾少军:建设以储能为核心、多能互补的新型能源体系[EB/OL]. (2023-7-31). https://www.nea.gov.cn/2023-07/31/c_1310734806.htm.
National energy administration. ZENG S J: Building a new energy system with energy storage as the core and multiple energy complementarity[EB/OL]. (2023-7-31).
[4] SHI J, WANG L H, LEE W-J, et al.Hybrid energy storage system (HESS) optimization enabling very short-term wind power generation scheduling based on output feature extraction[J]. Applied energy, 2019, 256: 113915.
[5] 孙舟, 田贺平, 王伟贤, 等. 梯次利用电池储能系统参与用户侧削峰填谷的经济性研究[J]. 太阳能学报, 2021, 42(4): 95-100.
SUN Z, TIAN H P, WANG W X, et al.Research on economy of echelon utilization battery energy storage system for user-side peak load shifting[J]. Acta energiae solaris sinica,2021,42(4): 95-100.
[6] BOCKLISCH T.Hybrid energy storage approach for renewable energy applications[J]. Journal of energy storage, 2016, 8: 311-319.
[7] BARELLI L, CIUPAGENU D A, OTTAVIANO A, et al.Stochastic power management strategy for hybrid energy storage systems to enhance large scale wind energy integration[J]. Journal of energy storage, 2020, 31: 101650.
[8] FAYE O, SZPUNAR J A.An efficient way to suppress the competition between adsorption of H₂ and desorption of nH₂-Nb complex from graphene sheet: a promising approach to H₂ storage[J]. The journal of physical chemistry C, 2018, 122(50): 28506-28517.
[9] HACATOGLU K, DINCER I, ROSEN M A.Sustainability of a wind-hydrogen energy system: assessment using a novel index and comparison to a conventional gas-fired system[J]. International journal of hydrogen energy, 2016, 41(19): 8376-8385.
[10] DAVID M, OCAMPO-MARTINEZ C, SÁNCHEZ-PEÑA R. Advances in alkaline water electrolyzers: a review[J]. Journal of energy storage, 2019, 23: 392-403.
[11] 杨胜, 樊艳芳, 侯俊杰, 等. 考虑平抑风光波动的ALK-PEM电解制氢系统容量优化模型[J]. 电力系统保护与控制, 2024, 52(1): 85-96.
YANG S, FAN Y F, HOU J J, et al.Capacity optimization model for an ALK-PEM electrolytic hydrogen production system considering the stabilization of wind and PV fluctuations[J]. Power system protection and control, 2024, 52(1): 85-96.
[12] 高超, 姚秀萍, 刘日新, 等. 基于自适应控制的风光制储氢协调运行策略研究[J]. 太阳能学报, 2023, 44(8): 102-109.
GAO C, YAO X P, LIU R X, et al.Research on coordinated operation strategy of wind-solar hydrogen production and storage based on adaptive control[J]. Acta energiae solaris sinica, 2023, 44(8): 102-109.
[13] 袁铁江,郭建华,杨紫娟,等.平抑风电波动的电-氢混合储能容量优化配置[J].中国电机工程学报,2024,44(4): 1397-1405.
YUAN T J, GUO J H, YANG Z J, et al.Optimal allocation of power electric-hydrogen hybrid energy storage of stabilizing wind power fluctuation[J]. Proceedings of the CSEE, 2024, 44(4): 1397-1405.
[14] 林俐, 郑馨姚, 周龙文. 基于燃氢燃气轮机的风光火储多能互补优化调度[J]. 电网技术, 2022, 46(8): 3007-3022.
LIN L, ZHENG X Y, ZHOU L W.Wind-PV-thermal-storage multi-energy complementary optimal dispatching based on hydrogen gas turbine[J]. Power system technology, 2022, 46(8): 3007-3022.
[15] 王永利, 向皓, 郭璐, 等. 面向多能互补的分布式光伏与电氢混合储能规划优化研究[J]. 电网技术, 2024, 48(2): 564-576.
WANG Y L, XIANG H, GUO L, et al.Research on planning optimization of distributed photovoltaic and electro-hydrogen hybrid energy storage for multi-energy complementarity[J]. Power system technology, 2024, 48(2): 564-576.
[16] 帅逸轩, 赵培轩, 刘慧敏, 等. 基于多功率耦合的风光互补制氢系统容量配置优化方法[J].太阳能学报, 2022, 43(11): 474-481.
SHUAI Y X, ZHAO P X, LIU H M et al. Optimization of battery capacity for wind-solar complementary hydrogen production system under multi-power conditions[J]. Acta energiae solaris sinica, 2022, 43(11): 474-481.
[17] 陈燚, 何山, 谢少华, 等. 基于合作博弈的风-光-电氢微网容量配置[J]. 太阳能学报, 2024, 45(2): 395-405.
CHEN Y, HE S, XIE S H, et al.Capacity configuration of wind-photovoltaic-electric hydrogen microgrid based on cooperative game[J]. Acta energiae solaris sinica, 2024, 45(2): 395-405.
[18] 李湃, 黄越辉, 张金平, 等. 多能互补发电系统电/热/氢储能容量协调优化配置[J]. 中国电机工程学报, 44(13): 5158-5168.
LI P, HUANG Y H, ZHANG J P, et al.Capacity coordinated optimization of battery, thermal and hydrogen storage system for multi-energy complementary power system[J]. Proceedings of the CSEE, , 44(13): 5158-5168.
[19] 高赐威, 王崴, 陈涛. 基于可逆固体氧化物电池的电氢一体化能源站容量规划[J]. 中国电机工程学报, 2022, 42(17): 6155-6170.
GAO C W WANG W, CHEN T. Capacity planning of electric-hydrogen integrated energy station based on reversible solid oxide battery[J].Proceedings of the CSEE, 2022, 42(17): 6155-6170.
[20] 李梓丘, 乔颖, 鲁宗相. 海上风电-氢能系统运行模式分析及配置优化[J]. 电力系统自动化, 2022, 46(8): 104-112.
LI Z Q, QIAO Y, LU Z X.Operation mode analysis and configuration optimization of offshore wind-hydrogen system[J]. Automation of electric power systems, 2022, 46(8): 104-112.
[21] DUTTA T, BHATTACHARYYA S, DEY S, et al.Border collie optimization[J]. IEEE access, 2020, 8: 109177-109197.
[22] JIANG G Q, YU F L, ZHAO Y.An analysis of vulnerability to agricultural drought in China using the expand grey relation analysis method[J]. Procedia engineering, 2012, 28: 670-676.