计及压缩空气储能爬坡能力的区域综合能源系统多时间尺度调度

李建华, 崔森, 张小龙, 郭俊波, 苏发万, 王聚鹏

分布式能源 ›› 2026, Vol. 11 ›› Issue (2) : 94-103.

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分布式能源 ›› 2026, Vol. 11 ›› Issue (2) : 94-103. DOI: 10.16513/j.2096-2185.DE.25100364
调度优化与市场机制

计及压缩空气储能爬坡能力的区域综合能源系统多时间尺度调度

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Multi-Timescale Scheduling of Regional Integrated Energy Systems Incorporating Compressed Air Energy Storage Ramp Capabilities

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摘要

为应对高比例新能源接入下区域综合能源系统面临的功率波动与爬坡需求挑战,聚焦先进绝热压缩空气储能(advanced adiabatic compressed air energy storage, AA-CAES)的爬坡支撑能力,构建计及AA-CAES爬坡能力的区域综合能源系统多时间尺度优化调度模型。首先,建立AA-CAES的运行模型,分析AA-CAES对火电爬坡的支撑能力;其次,提出计及AA-CAES爬坡能力的区域综合能源系统多时间尺度优化调度策略,长时间尺度优化在满足系统功率平衡的前提下,最小化区域综合能源系统的运行成本,短时间尺度采用模型预测控制方法实现功率的动态修正。算例仿真结果表明,计及AA-CAES爬坡能力的多时间尺度调度,可有效提升系统应对新能源波动的能力,避免火电频繁启停,同时降低运行成本、提升新能源消纳水平,为区域综合能源系统的经济稳定运行提供理论参考。

Abstract

To address the challenges of power fluctuations and ramping demands faced by regional integrated energy systems under high penetration of renewable energy, this paper focuses on the ramping support capability of advanced adiabatic compressed air energy storage (AA-CAES). A multi-timescale optimization dispatch model for regional integrated energy systems incorporating AA-CAES ramping capability is established. First, an operational model of AA-CAES is established to analyze its support capability for thermal power ramping. Second, a multi-timescale optimization dispatch strategy for regional integrated energy systems incorporating AA-CAES ramping capability is proposed. Long-timescale optimization minimizes operational costs while ensuring system power balance, and short-timescale dynamic power correction is achieved using model predictive control. Simulation results demonstrate that multi-timescale scheduling, incorporating AA-CAES ramping capability, effectively enhances the system’s resilience to renewable energy fluctuations, reduces thermal power dispatch requirements, lowers operational costs, and improves the integration of renewable energy. This approach provides theoretical guidance for the economic and stable operation of regional integrated energy systems.

关键词

区域综合能源系统 / 先进绝热压缩空气储能(AA-CAES) / 爬坡能力 / 多时间尺度 / 经济效益

Key words

regional integrated energy systems / advanced adiabatic compressed air energy storage (AA-CAES) / ramp capability / multi-timescale / economic benefits

引用本文

导出引用
李建华, 崔森, 张小龙, . 计及压缩空气储能爬坡能力的区域综合能源系统多时间尺度调度[J]. 分布式能源, 2026, 11(2): 94-103 https://doi.org/10.16513/j.2096-2185.DE.25100364.
LI Jianhua, CUI Sen, ZHANG Xiaolong, et al. Multi-Timescale Scheduling of Regional Integrated Energy Systems Incorporating Compressed Air Energy Storage Ramp Capabilities[J]. Distributed Energy, 2026, 11(2): 94-103 https://doi.org/10.16513/j.2096-2185.DE.25100364.
中图分类号: TK 02   

参考文献

[1]
新华网. 中共中央 国务院关于完整准确全面贯彻新发展理念做好碳达峰碳中和工作的意见[EB/OL]. (2021-10-24)[2025-05-07]. http://www.gov.cn/zhengce/202110/24/content_5644613.html.
Xinhua News Agency. Opinions of the Central Committee of the Communist Party of China and the State Council on fully, accurately and comprehensively implementing the new development concept and doing a good job in carbon peaking and carbon neutrality[EB/OL]. (2021-10-24)[2025-05-07]. http://www.gov.cn/zhengce/202110/24/content_5644613.html.
[2]
林玉鑫, 张京业. 海上风电的发展现状与前景展望[J]. 分布式能源, 2023, 8(2): 1-10.
LIN Yuxin , ZHANG Jingye . Development status and prospect of offshore wind power[J]. Distributed Energy, 2023, 8(2): 1-10.
[3]
倪佳华, 杨林刚, 陈来军, 等. 计及储能响应特性的混合储能系统容量优化配置[J]. 分布式能源, 2025, 10(6): 1-12.
NI Jiahua , YANG Lingang , CHEN Laijun , et al. Capacity optimization configuration of hybrid energy storage system considering energy storage response characteristics[J]. Distributed Energy, 2025, 10(6): 1-12.
[4]
张爱军, 刘石川, 慕腾, 等. 新能源发电富集地区输电系统规划方案的综合评价[J]. 智慧电力, 2025, 53(2): 16-24.
ZHANG Aijun , LIU Shichuan , MU Teng , et al. Comprehensive evaluation of transmission system planning schemes in renewable energy generation enrichment region[J]. Smart Power, 2025, 53(2): 16-24.
[5]
陈洁, 王樊云, 徐涛, 等. 电-碳市场下考虑风光不确定性的虚拟电厂优化调度[J]. 分布式能源, 2024, 9(4): 60-68.
CHEN Jie , WANG Fanyun , XU Tao , et al. Optimal scheduling of virtual power plant considering wind power and PV uncertainty in electric-carbon market[J]. Distributed Energy, 2024, 9(4): 60-68.
[6]
赵德福, 袁家海, 张健, 等. 多层次视角下颠覆性技术驱动的中国能源电力转型路径[J]. 电力建设, 2024, 45(8): 1-10.
ZHAO Defu , YUAN Jiahai , ZHANG Jian , et al. China’s energy and power system transition pathways driven by disruptive technologies: A multilevel perspective[J]. Electric Power Construction, 2024, 45(8): 1-10.
[7]
崔茗莉, 冯天天, 刘利利. 双碳目标下区块链与可再生能源的融合发展研究[J]. 智慧电力, 2024, 52(2): 17-24.
CUI Mingli , FENG Tiantian , LIU Lili . Integration and development of blockchain and renewable energy under double carbon target[J]. Smart Power, 2024, 52(2): 17-24.
[8]
王子晨, 刘瀚琛, 李建林, 等. 计及多层级储气布置的水下压缩空气储能配置策略[J]. 分布式能源, 2025, 10(6): 13-24.
WANG Zichen , LIU Hanchen , LI Jianlin , et al. Configuration strategy for underwater compressed air energy storage considering multi-level gas storage arrangement[J]. Distributed Energy, 2025, 10(6): 13-24.
[9]
HU J H , SARKER M R , WANG J H , et al. Provision of flexible ramping product by battery energy storage in day-ahead energy and reserve markets[J]. IET Generation,
[10]
东北能源监管局. 东北能源监管局综合施策推动解决电网爬坡能力不足问题[EB/OL]. (2025-07-11)[2025-08-25]. https://www.nea.gov.cn/20250711/6dcefafeea0c40e98f24f0d832dae47f/c.html.
Northeast Energy Regulatory Bureau. Comprehensive policies and measures to promote solving the problem of insufficient grid ramping capacity[EB/OL]. (2025-07-11)[2025-08-25]. https://www.nea.gov.cn/20250711/6dcefafeea0c40e98f24f0d832dae47f/c.html.
[11]
孙晓霞, 桂中华, 张新敬, 等. 压缩空气储能与可再生能源耦合研究进展[J]. 中国电机工程学报, 2023, 43(23): 9224-9241.
SUN Xiaoxia , GUI Zhonghua , ZHANG Xinjing , et al. Research progress on compressed air energy storage coupled with renewable energy[J]. Proceedings of the CSEE, 2023, 43(23): 9224-9241.
[12]
MAHFOUD R J , ALKAYEM N F , ZHANG Y Q , et al. Optimal operation of pumped hydro storage-based energy systems: A compendium of current challenges and future perspectives[J]. Renewable and Sustainable Energy Reviews, 2023, 178: 113267.
[13]
郭筱, 陈来军, 郭俊波, 等. 基于机会约束的先进绝热压缩空气储能系统容量配置策略[J]. 分布式能源, 2025, 10(6): 25-33.
GUO Xiao , CHEN Laijun , GUO Junbo , et al. Capacity configuration strategy for advanced adiabatic compressed air energy storage based on chance constraints[J]. Distributed Energy, 2025, 10(6): 25-33.
[14]
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 Tiejiang , GUO Jianhua , YANG Zijuan , 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.
[15]
王满商, 蒋力波, 许奕然, 等. 基于协调拓扑结构的可重构电池储能系统调频控制策略[J]. 分布式能源, 2025, 10(6): 54-61.
WANG Manshang , JIANG Libo , XU Yiran , et al. A frequency regulation control strategy for reconfigurable battery energy storage systems based on coordinated topological structures[J]. Distributed Energy, 2025, 10(6): 54-61.
[16]
刘笑驰, 梅生伟, 丁若晨, 等. 压缩空气储能工程现状、发展趋势及应用展望[J]. 电力自动化设备,
LIU Xiaochi , MEI Shengwei , DING Ruochen , et al. Current situation, development trend and application prospect of compressed air energy storage engineering projects[J]. Electric Power Automation Equipment,
[17]
HU S W , ZHANG X J , XU W Q , et al. Experimental study of tube-array-based liquid piston air compressor for near-isothermal compressed air energy storage system[J]. Applied Energy, 2024, 373: 123979.
[18]
梅生伟, 张通, 张学林, 等. 非补燃压缩空气储能研究及工程实践——以金坛国家示范项目为例[J]. 实验技术与管理,
MEI Shengwei , ZHANG Tong , ZHANG Xuelin , et al. Research and engineering practice of non-supplementary combustion compressed air energy storage: Taking Jintan national demonstration project as an example[J]. Experimental Technology and Management,
[19]
刘石, 杨毅, 黄正, 等. 基于模糊PID的水下压缩空气储能气囊压力波动抑制策略[J]. 分布式能源, 2025, 10(6): 34-42.
LIU Shi , YANG Yi , HUANG Zheng , et al. Pressure fluctuation suppression strategy of underwater compressed air energy storage airbag based on fuzzy PID[J]. Distributed Energy, 2025, 10(6): 34-42.
[20]
ZHANG X J , GAO Z Y , ZHOU B Q , et al. Advanced compressed air energy storage systems: Fundamentals and applications[J]. Engineering, 2024, 34: 246-269.
[21]
李广阔, 陈来军, 谢毓广, 等. 考虑压缩空气储能变工况特性的风储联合系统运行优化策略[J]. 高电压技术, 2020, 46(2): 511-518.
LI Guangkuo , CHEN Laijun , XIE Yuguang , et al. Coordinated optimization strategies of wind-storage hybrid system considering off-design characteristics of compressed air energy storage[J]. High Voltage Engineering, 2020, 46(2): 511-518.
[22]
崔森, 陈来军, 陈思源, 等. 基于最优动态功率补偿的先进绝热压缩空气储能一次调频控制策略[J]. 高电压技术, 2024, 50(6): 2433-2441.
CUI Sen , CHEN Laijun , CHEN Siyuan , et al. Primary frequency modulation control of advanced adiabatic compressed air energy storage based on optimal dynamic power compensation[J]. High Voltage Engineering, 2024, 50(6): 2433-2441.
[23]
亢丽君, 王蓓蓓, 薛必克, 等. 计及爬坡场景覆盖的高比例新能源电网平衡策略研究[J]. 电工技术学报, 2022, 37(13): 3275-3288.
KANG Lijun , WANG Beibei , XUE Bike , et al. Research on the balance strategy for power grid with high proportion renewable energy considering the ramping scenario coverage[J]. Transactions of China Electrotechnical Society, 2022, 37(13): 3275-3288.
[24]
GHARIBPOUR H , AMINIFAR F . Multi-stage equilibrium in electricity pool with flexible ramp market[J]. International Journal of Electrical Power & Energy Systems, 2019, 109: 661-671.
[25]
林顺富, 张琪, 沈运帷, 等. 面向灵活爬坡服务的高比例新能源电力系统可调节资源优化调度模型[J]. 电力系统保护与控制, 2024, 52(2): 90-100.
LIN Shunfu , ZHANG Qi , SHEN Yunwei , et al. Optimal dispatch model of adjustable resources in a power system with high proportion of renewable energy for flexible ramping product[J]. Power System Protection and Control, 2024, 52(2): 90-100.
[26]
王佳旭, 苗世洪, 王廷涛, 等. 考虑调峰-备用-爬坡-惯量多应用价值的大规模先进压缩空气储能多阶段优化规划[J]. 高电压技术, 2025, 51(3): 1339-1350.
WANG Jiaxu , MIAO Shihong , WANG Tingtao , et al. Multi-stage optimization planning of large-scale A-CAES with consideration of multi-application values including peak regulation, backup, ramping and inertia[J]. High Voltage Engineering, 2025, 51(3): 1339-1350.
[27]
魏佳, 石冰珂, 陈来军, 等. 面向直流馈入型电网调节需求的压缩空气储能两阶段鲁棒调度策略[J/OL]. 发电技术, 1-10(2025-07-11)[2025-08-30]. https://link.cnki.net/urlid/33.1405.TK.20250710.1646.002.
WEI Jia, SHI Bingke, CHEN Laijun, et al. Two-stage robust scheduling strategy of compressed air energy storage for regulation requirements in DC-feed power grids[J/OL]. Power Generation Technology, 1-10(2025-07-11)[2025-08-30]. https://link.cnki.net/urlid/33.1405.TK.20250710.1646.002.
[28]
林旗斌. 基于模型预测控制的含压缩空气储能微能网多时间尺度优化调度方法[J]. 电气技术,
LIN Qibin . Multi-time scale optimal scheduling strategy for micro energy network with compressed air energy storage based on model predictive control[J]. Electrical Engineering,
[29]
张时聪, 杨芯岩, 韩少锋, 等. 综合能源系统源-荷能量的多时间尺度预测[J]. 分布式能源, 2024, 9(4): 1-10.
ZHANG Shicong , YANG Xinyan , HAN Shaofeng , et al. Multi-timescale prediction of source-load energy in integrated energy system[J]. Distributed Energy, 2024, 9(4): 1-10.
[30]
LI T Y , CHEN L J , LIU H C , et al. Configuration optimization for advanced adiabatic compressed air energy storage considering thermal coupling characteristics[J]. Journal of Energy Storage, 2025, 131: 117249.
[31]
BAI J Y , WEI W , CHEN L J , et al. Modeling and dispatch of advanced adiabatic compressed air energy storage under wide operating range in distribution systems with renewable generation[J]. Energy, 2020, 206: 118051.

基金

中国三峡新能源(集团)股份有限公司科研项目(15044105)

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