中国矿业大学电气工程学院,江苏省徐州市 221116
王晓静(1999—),女,博士后,主要研究方向:综合能源系统优化调度。E-mail:dinger212@163.com
韩丽(1977—),女,通信作者,博士,教授,博士生导师,主要研究方向:可再生能源发电技术以及电网优化调度等。E-mail:dannyli717@163.com
袁志鑫(1998—),男,博士研究生,主要研究方向:综合能源系统优化调度。E-mail:2659020678@qq.com
收稿:2025-12-29,
修回:2026-06-05,
网络首发:2026-08-28,
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王晓静,韩丽,袁志鑫等.计及压缩空气储能系统响应时间特性的多时间尺度调度[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20251229004.
WANG Xiaojing,HAN Li,YUAN Zhixin,et al.Multi-timescale Scheduling Considering Response Time Characteristics of Compressed Air Energy Storage System[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20251229004.
王晓静,韩丽,袁志鑫等.计及压缩空气储能系统响应时间特性的多时间尺度调度[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20251229004. DOI:
WANG Xiaojing,HAN Li,YUAN Zhixin,et al.Multi-timescale Scheduling Considering Response Time Characteristics of Compressed Air Energy Storage System[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20251229004. DOI:
针对先进绝热压缩空气储能(advanced adiabatic compressed air energy storage
AA-CAES)系统动态响应特性与综合能源系统调度时间尺度不匹配的问题,提出了计及AA-CAES系统响应时间特性的综合能源系统多时间尺度调度策略。首先,建立含热响应延时的AA-CAES系统关键设备数学模型,分析膨胀机冷、温、热启动的响应时间差异,并从多个角度分析系统整体的响应时间特性。基于上述分析,在不同时间尺度下允许不同的状态切换及启动模式,建立多时间尺度调度模型。算例结果表明,所提策略实现了AA-CAES系统响应时间与调度尺度的匹配,与日前调度相比,实时调度阶段弃风功率峰值降低53.9%,切负荷功率峰值降低64.6%;全日弃风总量削减23.2%,切负荷总量削减45.2%,可充分发挥其电热双向调节能力以提升风电消纳水平,提高了AA-CAES系统并网调度的合理性和可靠性。
Aiming at the problem of mismatch between the dynamic response characteristics of the advanced adiabatic compressed air energy storage (AA-CAES) system and the scheduling time scale of the integrated energy system
a multi-timescale scheduling strategy for the integrated energy system considering the response time characteristics of the AA-CAES system is proposed. First
a mathematical model of the key equipment of the AA-CAES system with thermal response delay is established
the response time differences of the cold
warm
and hot start-up of the expander are analyzed
and the overall response time characteristics of the system are analyzed from multiple perspectives. Based on the above analysis
different state switching and start-up modes are allowed at different time scales
and a multi-timescale scheduling model is established. The case study results show that the proposed strategy achieves the matching between the response time of the AA-CAES system and the scheduling scale; compared with the day-ahead scheduling
in the real-time scheduling stage
the peak value of wind curtailment power is reduced by 53.9%
and the peak value of load shedding power is reduced by 64.6%; the total amount of wind curtailment throughout the day is reduced by 23.2%
and the total amount of load shedding is reduced by 45.2%
which can give full play to its electric-thermal bidirectional regulation capability to improve the level of wind power accommodation
and improve the rationality and reliability of the grid-connected scheduling of the AA-CAES system.
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