1.华驰动能(北京)科技有限公司,北京 101111
2.华北理工大学建筑工程学院
3.华北理工大学 冶金工程学院,河北 唐山 063210
4.河钢集团矿业有限公司,河北 唐山 063700
5.中国电子科技集团公司第十一研究所,北京 100015
卫宏强(1974—),男,硕士,工程师,研究方向为火力发电及飞轮储能,E-mail:651492845@qq.com;
曹斌,高级工程师,研究方向为光电与人工智能技术,E-mail:bincao11@163.com。
收稿:2025-10-15,
修回:2025-11-25,
纸质出版:2026-02-28
移动端阅览
卫宏强, 罗桂平, 张仕豪, 等. 基于"热-电-碳"三储综合能源系统参数设计及性能分析[J]. 储能科学与技术, 2026, 15(2): 503-515.
WEI Hongqiang, LUO Guiping, ZHANG Shihao, et al. Parameter design and performance analysis of the "thermal-electric-carbon" integrated energy system[J]. Energy Storage Science and Technology, 2026, 15(2): 503-515.
卫宏强, 罗桂平, 张仕豪, 等. 基于"热-电-碳"三储综合能源系统参数设计及性能分析[J]. 储能科学与技术, 2026, 15(2): 503-515. DOI: 10.19799/j.cnki.2095-4239.2025.0917.
WEI Hongqiang, LUO Guiping, ZHANG Shihao, et al. Parameter design and performance analysis of the "thermal-electric-carbon" integrated energy system[J]. Energy Storage Science and Technology, 2026, 15(2): 503-515. DOI: 10.19799/j.cnki.2095-4239.2025.0917.
本工作利用储热、蓄电和储碳装置的各自优势,对耦合碳捕集燃煤热电联产系统进行了参数优化设计,以350 MW燃煤热电联产机组为研究对象,提出了一种基于“热-电-碳”三储综合能源系统的改进麻雀优化算法。基于一天1440 min数据点,分别对碳捕集功率、储能容量以及充放策略进行研究。结果表明,改进后的麻雀优化算法能够满足全域范围的参数协同优化需求,采用储能装置可降低总成本9.44%,煤耗降低3.37%,热电调峰能力提升10%左右。通过“热-电-碳”储能装置的充放优化,得到了三种容量参数的最佳比例,即储碳容量为143 m
3
,储热容量为146.14 MWh,蓄电容量为62.61 MWh,该参数组合能够有效减少负荷波动,使其维持在最经济负荷区间。此外,分别对动力煤、蓄电池、储热罐以及储碳罐市场价格进行了敏感性分析,结果显示,动力煤价格对系统总成本影响最显著,其次为储碳罐价格波动、储热罐单价波动最后为蓄电池单价波动。本研究有助于推动多储能系统参数协同优化的应用,为综合能源系统参数设计及运行策略的研究提供参考。
By leveraging the complementary functions of heat storage
electrical energy storage
and carbon storage devices
this study investigates the parameter optimization of a coupled carbon-capture coal-fired cogeneration system. A 350 MW coal-fired cogeneration unit is selected as the case study
and an improved sparrow optimization algorithm is proposed within the framework of a "heat-electricity-carbon" integrated energy storage system. Using high-resolution operational data comprising 1440 data points per day
the coordinated optimization of carbon-capture power
energy storage capacities
and charging-discharging strategies is systematically analyzed. The results demonstrate that the improved sparrow optimization algorithm effectively satisfies collaborative parameter optimization requirements across the full operating range. The integration of energy storage devices reduces total system cost by 9.44%
decreases coal consumption by 3.37%
and enhances thermal power peak-regulation capacity by approximately 10%. Through optimized charging and discharging of the heat-electricity-carbon storage system
the optimal capacity configuration is determined as 143 m³ for carbon storage
146.14 MW·h for heat storage
and 62.61 MW·h for electrical energy storage. This configuration effectively mitigates load fluctuations and maintains system operation within the most economical load range. Furthermore
sensitivity analyses of thermal coal prices
battery costs
heat storage tank prices
and carbon storage tank prices indicate that thermal coal price exerts the greatest influence on total system cost
followed by carbon storage tank price
heat storage tank price
and battery price. Overall
this study supports the practical application of coordinated parameter optimization for multi-energy storage systems and provides valuable guidance for the design and operational optimization of integrated energy systems.
代宇涵, 刘春, 周朋, 等. 双碳背景下电力系统储能技术的应用与研究进展[J]. 储能科学与技术, 2024, 13(8): 2772-2774. DOI:10.19799/j.cnki.2095-4239.2024.0695.
DAI Y H, LIU C, ZHOU P, et al. Application and research progress of energy storage technology in power systems under the dual carbon background[J]. Energy Storage Science and Technology, 2024, 13(8): 2772-2774. DOI:10.19799/j.cnki.2095-4239.2024.0695.
本刊编辑部. «2025年能源工作指导意见»发布 非化石能源消费占比目标提至20%左右[J]. 农村电工, 2025, 33(4): 1. DOI:10.16642/j.cnki.ncdg.2025.04.002.
朱棪, 徐斌. 岛域燃煤电厂碳捕集系统运行及经济性研究[J]. 环境工程学报, 2025, 19(8): 1934-1942. DOI:10.12030/j.cjee.202409146.
ZHU Y, XU B. Study on the operation and economics of carbon capture system in island Coal-Fired power plants[J]. Chinese Journal of Environmental Engineering, 2025, 19(8): 1934-1942. DOI:10.12030/j.cjee.202409146.
闫亚龙, 张进华, 黄艳, 等. 火电机组深度调峰背景下储热技术应用现状及进展[J]. 洁净煤技术, 2025, 31(S1): 495-506. DOI:10.13226/j.issn.1006-6772.25021001.
YAN Y L, ZHANG J H, HUANG Y, et al. Current status and progress of heat storage technology application under background of deep peak shaving of thermal power units[J]. Clean Coal Technology, 2025, 31(S1): 495-506. DOI:10.13226/j.issn.1006-6772.25021001.
施卫华. 电力储能发展现状及能效提升策略与探索[J]. 电工技术, 2025(9): 1-6, 11. DOI:10.19768/j.cnki.dgjs.2025.09.001.
SHI W H. Energy storage development status and energy efficiency improvement strategies and exploration[J]. Electric Engineering, 2025(9): 1-6, 11. DOI:10.19768/j.cnki.dgjs.2025.09.001.
胡健, 任育杰, 杜金魁, 等. 含相变储能的风/光/热电联产综合能源系统优化调度[J]. 储能科学与技术, 2023, 12(3): 968-975. DOI:10.19799/j.cnki.2095-4239.2022.0515.
HU J, REN Y J, DU J K, et al. Optimal scheduling of an integrated wind/solar/gas cogeneration energy system with phase change energy storage[J]. Energy Storage Science and Technology, 2023, 12(3): 968-975. DOI:10.19799/j.cnki.2095-4239.2022.0515.
李昊, 刘畅, 苗博, 等. 考虑冷热电互补及储能系统的多园区综合能源系统协调优化调度[J]. 储能科学与技术, 2022, 11(5): 1482-1491. DOI:10.19799/j.cnki.2095-4239.2021.0631.
LI H, LIU C, MIAO B, et al. Coordinative optimal dispatch of multi-park integrated energy system considering complementary cooling, heating and power and energy storage systems[J]. Energy Storage Science and Technology, 2022, 11(5): 1482-1491. DOI:10.19799/j.cnki.2095-4239.2021.0631.
王君梅, 吴晓南, 廖柏睿. 考虑环境惩罚的综合能源系统多季节优化研究[J]. 储能科学与技术, 2024, 13(10): 3720-3729. DOI:10.19799/ j.cnki.2095-4239.2024.0340.
WANG J M, WU X N, LIAO B R. Multi-season optimization of integrated energy systems considering environmental penalties[J]. Energy Storage Science and Technology, 2024, 13(10): 3720-3729. DOI:10.19799/j.cnki.2095-4239.2024.0340.
智筠贻, 凌浩恕, 吴昊, 等. 风光储多能互补能源系统容量配置优化[J]. 储能科学与技术, 2024, 13(11): 3874-3888. DOI:10.19799/j.cnki.2095-4239.2024.0377.
ZHI J Y, LING H S, WU H, et al. Optimization of capacity configuration for multi-energy complementary systems using wind, solar, and energy storage[J]. Energy Storage Science and Technology, 2024, 13(11): 3874-3888. DOI:10.19799/j.cnki.2095-4239.2024.0377.
丁娅鑫, 熊军华. 基于改进麻雀算法的区域综合能源系统优化研究[J]. 自动化与仪表, 2022, 37(10): 24-29, 34. DOI:10.19557/j.cnki.1001-9944.2022.10.005.
DING Y X, XIONG J H. Research on regional integrated energy system optimization based on improved sparrow algorithm[J]. Automation & Instrumentation, 2022, 37(10): 24-29, 34. DOI:10.19557/j.cnki.1001-9944.2022.10.005.
王建军. 内蒙古一自备电厂1#炉顶棚过热器泄漏失效分析[J]. 内蒙古石油化工, 2017, 43(2): 46-47. DOI:10.3969/j.issn.1006-7981.2017.02.019.
WANG J J. Failure analysis of the leakage in the superheater roof of unit 1 in an Inner Mongolia self-powered power plant[J]. Inner Mongolia Petrochemical Industry, 2017, 43(2): 46-47. DOI:10.3969/j.issn.1006-7981.2017.02.019.
陈吉玲. 压缩空气储能系统与火电机组耦合方案及其特性研究[D]. 北京: 华北电力大学, 2021.CHEN J L. Research on coupling scheme and characteristics of compressed air energy storage system and thermal power unit[D]. Beijing: North China Electric Power University, 2021.
马文澍. 热电联产机组能耗特性分析及负荷优化分配研究[D]. 吉林: 东北电力大学, 2023.MA W S. The analysis of energy consumption characteristics and research on optimal load dispatch of cogeneration units[D]. Jilin: Northeast Dianli University, 2023.
SUN J, MA S C, HUO C, et al. An improved calculation method of coal consumption index for heating in CHP with a high back pressure turbine[J]. IOP Conference Series: Earth and Environmental Science, 2021, 661(1): 012017. DOI:10.1088/1755-1315/661/1/012017.
胡东子. 压缩二氧化碳储能与碳捕集燃煤机组的耦合系统性能研究[D ] . 北京: 华北电力大学, 2023.HU D Z. Performance study of coupled system for compressed CO 2 energy storage and carbon capture coal-fired units[D ] . Beijing: North China Electric Power University, 2023.
王金星, 俞卫新. 碳捕集系统与燃煤机组耦合技术[M]. 北京: 中国电力出版社, 2023.WANG J X, YU W X. Carbon capture system coupling technology for coal-fired units[M]. Beijing: China Electric Power Press, 2023.
STANEK B, OCHMANN J, BARTELA Ł, et al. Isobaric tanks system for carbon dioxide energy storage–The performance analysis[J]. Journal of Energy Storage, 2022, 52: 104826. DOI:10.1016/j.est.2022.104826.
杨利, 刘永林, 房伟, 等. 配置储热罐后热电联产机组运行优化[J]. 热力发电, 2020, 49(4): 70-76. DOI:10.19666/j.rlfd.201909227.
YANG L, LIU Y L, FANG W, et al. Operation optimization of cogeneration unit equipped with heat accumulator[J]. Thermal Power Generation, 2020, 49(4): 70-76. DOI:10.19666/j.rlfd.201909227.
张婉滢, 金晶, 解小军, 等. 熔盐储热辅助低压缸零出力机组深度调峰的应用分析[J]. 太阳能学报, 2025, 46(1): 279-287. DOI:10.19912/j.0254-0096.tynxb.2023-1504.
ZHANG W Y, JIN J, XIE X J, et al. Application analysis of deep peak shaving of low-pressure cylinder zero-output unit assisted by molten salt heat storage[J]. Acta Energiae Solaris Sinica, 2025, 46(1): 279-287. DOI:10.19912/j.0254-0096.tynxb.2023-1504.
石冰斓, 程远达, 尹富强, 等. 基于分布式蓄热的热电联产供热系统节能优化研究[J/OL]. 太原理工大学学报, 1-11[2026-01-05].https://link.cnki.net/urlid/14.1220.N.20240510.1040.002.
王子杰. 热电联产机组运行能效及灵活性提升关键技术研究[D]. 北京: 华北电力大学, 2024.
ZHANG Y, SUN L, MA F, et al. Collaborative optimization of the battery capacity and sailing speed considering multiple operation factors for a battery-powered ship[J]. World Electric Vehicle Journal, 2022, 13(2): 40. DOI:10.3390/wevj13020040.
向翩翩. 碳中和目标下中国合成氨脱碳路径及应用潜力和布局分析研究[D]. 北京: 北京工业大学, 2023.XIANG P P. Study on the decarbonization pathway and potential application and layout analysis of ammonia industry in China under the carbon neutrality target[D]. Beijing: Beijing University of Technology, 2023.
XUE J K, SHEN B. A novel swarm intelligence optimization approach: Sparrow search algorithm[J]. Systems Science & Control Engineering, 2020, 8(1): 22-34. DOI:10.1080/21642583.2019.1708830.
郭庆辉, 李媛, 杨东升. 一种改进麻雀搜索算法的收敛性分析及应用[J]. 控制与决策, 2024, 39(8): 2502-2510. DOI:10.13195/j.kzyjc.2023.1065.
GUO Q H, LI Y, YANG D S. Convergence analysis and application of an improved sparrow search algorithm[J]. Control and Decision, 2024, 39(8): 2502-2510. DOI:10.13195/j.kzyjc. 2023.1065.
周明哲, 富海鹰, 赵炎炎, 等. 一种改进麻雀优化算法在岩体结构面分组中的应用[J]. 长江科学院院报, 2025, 42(11): 133-140. DOI:10.11988/ckyyb.20240931.
ZHOU M Z, FU H Y, ZHAO Y Y, et al. Application of an improved sparrow search algorithm in grouping rock mass structural planes[J]. Journal of Yangtze River Scientific Research Institute, 2025, 42(11): 133-140. DOI:10.11988/ckyyb.20240931.
FENG H, ZHOU H, CAO D H, et al. Data-driven hydraulic pressure prediction for typical excavators using a new deep learning SCSSA-LSTM method[J]. Expert Systems with Applications, 2025, 275: 127078. DOI:10.1016/j.eswa.2025.127078.
FENG J Q, CAI F, ZHAN X J, et al. Multi-timescale inconsistency evaluation and data-driven state of health prediction for circulating water-cooled series battery pack[J]. Measurement, 2025, 242: 115982. DOI:10.1016/j.measurement.2024.115982.
YANG X Y, ZHOU G F, REN Z J, et al. High-precision air conditioning load forecasting model based on improved sparrow search algorithm[J]. Journal of Building Engineering, 2024, 92: 109809. DOI:10.1016/j.jobe.2024.109809.
陈致远, 曾国辉, 赵晋斌. 基于改进麻雀算法的直流微电网分级均流稳压控制[J]. 电气工程学报, 2025, 20(1): 317-327. DOI:10.11985/2025.01.031.
CHEN Z Y, ZENG G H, ZHAO J B. Grading current sharing and voltage stabilizing control of DC microgrid based on improved sparrow search algorithm[J]. Journal of Electrical Engineering, 2025, 20(1): 317-327. DOI:10.11985/2025.01.031.
国家能源局. 关于印发«关于发展热电联产的规定»的通知[EB/OL]. (2012-01-04)[2025-03-12].
国家发展改革委, 能源局, 财政部, 住房城乡建设部, 环境保护部关于印发«热电联产管理办法»的通知[J]. 中华人民共和国国务院公报, 2016(20): 67-72.
0
浏览量
11
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010102001997号