大型新能源基地综合能源系统协同设计

高翔 ,  周志成 ,  何佳熹 ,  张书帜 ,  张兄文

西安交通大学学报 ›› 2026, Vol. 60 ›› Issue (8) : 123 -135.

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西安交通大学学报 ›› 2026, Vol. 60 ›› Issue (8) : 123 -135. DOI: 10.7652/xjtuxb202608011
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大型新能源基地综合能源系统协同设计

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Collaborative Design of Integrated Energy Systems for Large-Scale Renewable Energy Bases

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摘要

针对大型新能源基地在风光资源波动、时序分布不均及外送约束条件下的新能源消纳、供能可靠性与运行经济性问题,开展电热氢氨综合能源系统协同设计与运行特性研究。首先,建立涵盖风光发电、火电、熔盐储热、电解制氢、合成氨及多类型储能的综合能源系统模型。提出基于连续时间窗口划分的典型场景生成方法,构建配置-调度协同的双层嵌套优化框架。采用基于边界审查机制的区域收缩求解算法,实现高维度、大尺寸空间下系统容量配置与多场景运行特性的协同优化。最后,对传统风光火储系统和电热氢氨综合能源系统开展优化与仿真对比分析。结果显示,引入氢氨子系统后,可再生能源占比提高7.28%,弃电率降低35.3%,燃煤成本与碳排放成本同步下降17.6%,单位能量净成本降低0.023元/(kW·h)。同时,系统年度运行特性受季节差异影响显著,冬季风电增强改善系统经济性,夏季光伏富集增大消纳压力。相比之下,电热氢氨系统通过多能转化与外送维持更优的消纳水平和运行经济性。敏感性分析表明,随着氢价上升,系统配置策略由规模扩张逐步转向效能优化,从而实现单位能量收益提升。

Abstract

To address the challenges of renewable energy accommodation, supply reliability, and operational economy in large-scale renewable energy bases under wind-solar resource fluctuations, uneven temporal distribution, and power export constraints, the coordinated design and operational characteristics of an electricity-heat-hydrogen-ammonia integrated energy system were investigated. An integrated system model covering wind power generation, photovoltaic power generation, thermal power, molten-salt thermal storage, water electrolysis, ammonia synthesis, and multiple types of energy storage was established. A typical scenario generation method based on continuous time-window partitioning was developed, and a bi-level nested optimization framework integrating capacity configuration and dispatch was constructed. A boundary contraction inspection-based regional search algorithm was adopted to achieve the collaborative optimization of system capacity configuration and multi-scenario operational characteristics in a high-dimensional, large-scale solution space. Comparative optimization and simulation analyses were conducted for a conventional wind-solar-coal-storage system and the proposed system. The results show that introducing the hydrogen-ammonia subsystem increases the renewable energy share by 7.28%, reduces the curtailment rate by 35.3%, decreases coal consumption and carbon emission costs by 17.6%, and lowers the net unit energy cost by 0.023 yuan/(kW·h). Seasonal differences significantly affect system operation, with enhanced wind power in winter improving economic performance, while abundant solar power in summer intensifies accommodation pressure. In contrast, the electricity-heat-hydrogen-ammonia system achieves superior accommodation levels and operational economy through multi-energy conversion and power export. Sensitivity analysis further shows that rising hydrogen prices shift the configuration strategy from scale expansion toward efficiency optimization, thereby increasing unit energy revenue.

关键词

大型新能源基地 / 综合能源系统 / 协同设计 / 电解制氢 / 合成氨

Key words

large-scale renewable energy base / integrated energy system / coordinated design / electrolysis hydrogen production / ammonia synthesis

引用本文

引用格式 ▾
高翔,周志成,何佳熹,张书帜,张兄文. 大型新能源基地综合能源系统协同设计[J]. 西安交通大学学报, 2026, 60(8): 123-135 DOI:10.7652/xjtuxb202608011

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参考文献

[1]

Zhang Xiaoye, Zhong Junting, Zhang Xiliang, et al. China can achieve carbon neutrality in line with the Paris agreement’s 2℃ target: navigating global emissions scenarios, warming levels, and extreme event projections[J]. Engineering, 2025, 44: 207-214.

[2]

国家发展和改革委员会, 国家能源局. 关于印发《“十四五”现代能源体系规划》的通知: 发改能源〔2022〕210号[EB/OL]. (2022—01—29) [2026—01—01].https://www.ndrc.gov.cn/xxgk/zcfb/ghwb/202203/t20220322_1320016.html.

[3]

国家能源局. 国家能源局关于促进新能源集成融合发展的指导意见: 国能发新能〔2025〕93号[EB/OL]. (2025—10—31) [2026—01—01].https://www.gov.cn/zhengce/zhengceku/202511/content_7048396.htm.

[4]

国家发展和改革委员会, 国家能源局. 以沙漠、戈壁、荒漠地区为重点的大型风电光伏基地规划布局方案: 发改基础〔2022〕195号[R].北京: 中华人民共和国国家发展和改革委员会, 2022.

[5]

王杨, 罗抒予, 姚凌翔, . 面向大型新能源基地的太阳能光热发电规划研究综述: 场景、模型与发展方向[J]. 电网技术, 2025, 49(7): 2712-2724.

[6]

Wang Yang, Luo Shuyu, Yao Lingxiang, et al. A review of concentrating solar power planning for large—scale renewable energy bases: scenarios, models and development perspectives[J]. Power System Technology, 2025, 49(7): 2712-2724.

[7]

卓振宇, 张宁, 谢小荣, . 高比例可再生能源电力系统关键技术及发展挑战[J]. 电力系统自动化, 2021, 45(9): 171-191.

[8]

Zhuo Zhenyu, Zhang Ning, Xie Xiaorong, et al. Key technologies and developing challenges of power system with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2021, 45(9): 171-191.

[9]

李明轩, 范越, 汪莹, . 新能源大基地风光储容量协调优化配置[J]. 电力自动化设备, 2024, 44(3): 1-8.

[10]

Li Mingxuan, Fan Yue, Wang Ying, et al. Coordinated optimal configuration of wind—photovoltaic—energy storage capacity for large—scale renewable energy bases[J]. Electric Power Automation Equipment, 2024, 44(3): 1-8.

[11]

刘泽洪, 周原冰, 金晨. 支撑新能源基地电力外送的电源组合优化配置策略研究[J]. 全球能源互联网, 2023, 6(2): 101-112.

[12]

Liu Zehong, Zhou Yuanbing, Jin Chen. Optimization strategy study on installation mix of renewable energy power base for supporting outbound delivery[J]. Journal of Global Energy Interconnection, 2023, 6(2): 101-112.

[13]

李昕媛, 任康, 郑霞忠. 中国清洁能源基地多时间尺度互补网络及鲁棒性研究[J]. 太阳能学报, 2025, 46(7): 307-317.

[14]

Li Xinyuan, Ren Kang, Zheng Xiazhong. Study on multi—time scale complementary networks and robustness in China’s clean energy bases[J]. Acta Energiae Solaris Sinica, 2025, 46(7): 307-317.

[15]

张沈习, 王丹阳, 程浩忠, . 双碳目标下低碳综合能源系统规划关键技术及挑战[J]. 电力系统自动化, 2022, 46(8): 189-207.

[16]

Zhang Shenxi, Wang Danyang, Cheng Haozhong, et al. Key technologies and challenges of low—carbon integrated energy system planning for carbon emission peak and carbon neutrality[J]. Automation of Electric Power Systems, 2022, 46(8): 189-207.

[17]

Guo Siyi, Ren Fukang, Wei Ziqing, et al. A multi—objective collaborative planning method for a PV—powered hybrid energy system considering source—load matching[J]. Energy Conversion and Management, 2024, 316: 118848.

[18]

Kourougianni Fanourios, Arsalis Alexandros, Olympios Andreas V, et al. A comprehensive review of green hydrogen energy systems[J]. Renewable Energy, 2024, 231: 120911.

[19]

茆美琴, 陶伟鹏, 武继训, . 基于风光概率预测的可再生能源制氨系统容量优化配置方法[J]. 太阳能学报, 2025, 46(8): 644-655.

[20]

Mao Meiqin, Tao Weipeng, Wu Jixun, et al. Capacity configuration optimization for renewable power ammonia production system based on wind and solar probability prediction[J]. Acta Energiae Solaris Sinica, 2025, 46(8): 644-655.

[21]

韩旭, 赵文强, 范彩兄, . 火电机组耦合多级熔盐储热系统热力学性能研究[J]. 热能动力工程, 2025, 40(7): 106-112.

[22]

Han Xu, Zhao Wenqiang, Fan Caixiong, et al. Research on thermodynamic performance of multi—stage molten salt thermal storage system coupled with thermal power units[J]. Journal of Engineering for Thermal Energy and Power, 2025, 40(7): 106-112.

[23]

李建林, 孙浩元, 张敏慧, . 计及风电平抑的电—氢混合储能容量优化配置[J]. 太阳能学报, 2025, 46(6): 120-129.

[24]

Li Jianlin, Sun Haoyuan, Zhang Minhui, et al. Optimal capacity allocation of electricity—hydrogen hybrid energy storage considering wind power smoothing[J]. Acta Energiae Solaris Sinica, 2025, 46(6): 120-129.

[25]

林啸龙, 刘涛, 孟宪宸, . 风光火储耦合氢储能系统的制储氢容量优化和可行性分析[J]. 西安交通大学学报, 2026, 60(3): 122-131.

[26]

Lin Xiaolong, Liu Tao, Meng Xianchen, et al. Optimization of hydrogen production and storage capacity and feasibility analysis of wind—solar—thermal—storage coupled hydrogen energy storage system[J]. Journal of Xi’an Jiaotong University, 2026, 60(3): 122-131.

[27]

Gao Xiang, Lin Hua, Jing Dengwei, et al. A novel framework for optimal design of solar—powered integrated energy system considering long timescale characteristics[J]. Energy, 2025, 325: 136137.

[28]

Tangi Marco, Amaranto Alessandro. Designing integrated and resilient multi—energy systems via multi—objective optimization and scenario analysis[J]. Applied Energy, 2025, 382: 125281.

[29]

Gao Xiang, Lin Hua, Jing Dengwei, et al. Multi—objective energy management of solar—powered integrated energy system under forecast uncertainty based on a novel dual—layer correction framework[J]. Solar Energy, 2024, 281: 112902.

[30]

国家发展和改革委员会. 关于2021年新能源上网电价政策有关事项的通知: 发改价格〔2021〕833号[EB/OL]. (2021—06—11) [2026—01—01].https://www.ndrc.gov.cn/xxgk/zcfb/tz/202106/t20210611_1283088.html.

[31]

中国氢能联盟研究院. 中国氢价指数年度报告(2025年版)[R/OL].2025—05—06. https://www.chinah2data.com/file/bigdata—docs/abf4693f203451e9a903ec5b5f290579.pdf.

[32]

余志鹏, 林今, 雷金勇, . 考虑火电掺氢氨燃烧发电的受端电力系统多阶段减碳规划[J]. 电力系统自动化, 2025, 49(5): 57-68.

[33]

Yu Zhipeng, Lin Jin, Lei Jinyong, et al. Multi—stage decarbonization planning for receiving—end power systems considering thermal power generation with hydrogen—ammonia cofiring[J]. Automation of Electric Power Systems, 2025, 49(5): 57-68.

[34]

韩培东, 王伟胜, 李湃, . 基于多目标优化的大型新能源基地风光储容量联合规划配置[J]. 电网技术, 2025, 49(11): 4477-4485.

[35]

Han Peidong, Wang Weisheng, Li Pai, et al. Joint planning and configuration of wind—solar—storage capacity for large—scale renewable energy bases based on multi—objective optimization[J]. Power System Technology, 2025, 49(11): 4477-4485.

[36]

金昱烨, 方家琨, 艾小猛, . 含季节性氢储能的电力系统跨尺度全年时序生产模拟方法[J]. 电力系统自动化, 2025, 49(14): 120-129.

[37]

Jin Yuye, Fang Jiakun, Ai Xiaomeng, et al. Cross—time—scale annual chronological production simulation method for power system with seasonal hydrogen energy storage[J]. Automation of Electric Power Systems, 2025, 49(14): 120-129.

[38]

张彦虎, 汪慧, 邹绍琨, . 多因素约束下源—储—荷协同的风储氢氨优化配置策略研究[J]. 储能科学与技术, 2025, 14(6): 2558-2566.

[39]

Zhang Yanhu, Wang Hui, Zou Shaokun, et al. Optimal allocation strategy of wind hydrogen and ammonia storage under multi—factor constraints of source—storage—load cooperation[J]. Energy Storage Science and Technology, 2025, 14(6): 2558-2566.

[40]

魏乐, 周家俊, 张怡, . 耦合熔盐储热火电机组技术经济分析与运行优化[J]. 工程热物理学报, 2026, 47(1): 46-58.

[41]

Wei Le, Zhou Jiajun, Zhang Yi, et al. Techno—economic analysis and operation optimization of thermal power units coupled with molten salt heat storage[J]. Journal of Engineering Thermophysics, 2026, 47(1): 46-58.

基金资助

国家重点研发计划资助项目(2024YFB4007400)

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