考虑输电约束的风力发电系统压缩空气储能可靠性与经济性评价

doi:10.19799/j.cnki.2095-4239.2024.0489

摘要/Abstract

摘要：

压缩空气储能被视为一种可行的方案，用来解决风力发电中的可变性和不确定性问题。储能系统的运营策略取决于当前的市场和监管环境，这将直接影响整个系统在质量、可靠性、效率和环保方面的表现。压缩空气储能系统可以独立运行，以利润最大化，也可以与风力发电协同运行，以充分利用可再生能源，并实现市场共赢。本文探讨了压缩空气储能在输电约束型风力综合发电系统中的应用和潜在收益。本文开发了综合模型，用于优化风能和压缩空气储能的运营策略，并量化了压缩空气储能对系统可靠性、效率和环保目标的贡献。研究结果显示了在不同方面平衡压缩空气储能的潜在收益。所提出的方法和分析结果可为公用事业单位提供有价值的参考，以制定有效的监管框架，推动大规模储能的整合，有效支持未来可再生能源的发展，同时确保可靠供应给电力消费者。

关键词: 压缩空气储能, 储能系统, 输电约束型, 风能, 潜在效益

Abstract:

Compressed air energy storage (CAES) is recognized as a viable solution to address variability and uncertainty in wind power generation. The performance of energy storage systems is significantly influenced by market conditions and regulatory frameworks, which directly affect the system's quality, reliability, efficiency, and environmental impact. CAES systems can operate independently to maximize profit or in synergy with wind power generation to fully utilize renewable energy resources, thereby achieving mutual benefits in the market. This study investigates the application and potential advantages of CAES in wind power systems with transmission constraints. A comprehensive model is developed to optimize operational strategies for wind energy and CAES, assessing the contributions of CAES to system reliability, efficiency, and environmental goals. The results highlight the benefits of integrating CAES in balancing wind power, enhancing system performance across various metrics. The proposed methods and findings offer valuable guidance for utilities and policymakers in formulating effective regulatory frameworks, promoting large-scale energy storage integration, supporting the expansion of renewable energy, and ensuring a reliable power supply for consumers.

Key words: compressed air energy storage, energy storage system, transmission constraint, wind energy, potential benefit

中图分类号:

TM 61

贺鸿鹏, 王小宇, 徐美娇, 马成龙, 张伟, 张丽. 考虑输电约束的风力发电系统压缩空气储能可靠性与经济性评价[J]. 储能科学与技术, 2024, 13(11): 4226-4234.

Hongpeng HE, Xiaoyu WANG, Meijiao XU, Chenglong MA, Wei ZHANG, Li ZHANG. Reliability and economic evaluation of compressed air energy storage in wind power generation systems with transmission constraints[J]. Energy Storage Science and Technology, 2024, 13(11): 4226-4234.

图/表 11

图1

图2

图3

图4

图5

表1

表2

表3

图6

图7

图8

参考文献 32

1	吴政球, 干磊, 曾议, 等. 风力发电最大风能追踪综述[J]. 电力系统及其自动化学报, 2009, 21(4): 88-93. DOI: 10.3969/j.issn.1003-8930.2009.04.017.
	WU Z Q, GAN L, ZENG Y, et al. Summary of tracking the largest wind energy for wind power generation[J]. Proceedings of the CSU-EPSA, 2009, 21(4): 88-93. DOI: 10.3969/j.issn.1003-8930. 2009.04.017.
2	李佳佳, 李兴朔, 魏凡超, 等. 耦合火电机组的新型压缩空气储能系统技术经济性评估研究[J]. 中国电机工程学报, 2023, 43(23): 9171-9183. DOI: 10.13334/j.0258-8013.pcsee.222819.
	LI J J, LI X S, WEI F C, et al. Research on techno-economic evaluation of new type compressed air energy storage coupled with thermal power unit[J]. Proceedings of the CSEE, 2023, 43(23): 9171-9183. DOI: 10.13334/j.0258-8013.pcsee.222819.
3	钟伟杰, 唐俊杰, 孙青, 等. 计及压缩空气储能的发输电系统可靠性评估[J]. 电力系统自动化, 2023, 47(8): 145-155. DOI: 10.7500/AEPS20220309010.
	ZHONG W J, TANG J J, SUN Q, et al. Reliability evaluation of power generation and transmission system considering compressed air energy storage[J]. Automation of Electric Power Systems, 2023, 47(8): 145-155. DOI: 10.7500/AEPS20220309010.
4	赵靖英, 乔珩埔, 姚帅亮, 等. 考虑储能SOC自恢复的风电波动平抑混合储能容量配置策略[J]. 电工技术学报, 2024, 39(16): 5206-5219. DOI: 10.19595/j.cnki.1000-6753.tces.230915.
	ZHAO J Y, QIAO H P, YAO S L, et al. Hybrid energy storage system capacity configuration strategy for stabilizing wind power fluctuation considering SOC self-recovery[J]. Transactions of China Electrotechnical Society, 2024, 39(16): 5206-5219. DOI: 10.19595/j.cnki.1000-6753.tces.230915.
5	ZHANG Y, ZHU S Z, CHOWDHURY A A. Reliability modeling and control schemes of composite energy storage and wind generation system with adequate transmission upgrades[J]. IEEE Transactions on Sustainable Energy, 2011, 2(4): 520-526. DOI: 10.1109/TSTE.2011.2160663.
6	LOISEL R, MERCIER A, GATZEN C, et al. Valuation framework for large scale electricity storage in a case with wind curtailment[J]. Energy Policy, 2010, 38(11): 7323-7337.
7	ARMAN S I, KARKI R, BILLINTON R. Resource strength and location impact of wind power on bulk electric system reliability[C]//2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). October 16-20, 2016, Beijing, China. IEEE, 2016: 1-6. DOI: 10.1109/PMAPS. 2016. 7764058.
8	步天龙, 寇汉鹏, 李迪, 等. 含储能有源配网的经济调度与协同优化[J]. 现代电力, 2024, 41(3): 421-430. DOI: 10.19725/j.cnki.1007-2322.2022.0343.
	BU T L, KOU H P, LI D, et al. Economic dispatching and collaborative optimization of active distribution network with energy storage[J]. Modern Electric Power, 2024, 41(3): 421-430. DOI: 10.19725/j.cnki.1007-2322.2022.0343.
9	尹斌鑫, 苗世洪, 李姚旺, 等. 先进绝热压缩空气储能在综合能源系统中的经济性分析方法[J]. 电工技术学报, 2020, 35(19): 4062-4075. DOI: 10.19595/j.cnki.1000-6753.tces.191064.
	YIN B X, MIAO S H, LI Y W, et al. Study on the economic analysis method of advanced adiabatic compressed air energy storage in integrated energy system[J]. Transactions of China Electrotechnical Society, 2020, 35(19): 4062-4075. DOI: 10.19595/j.cnki.1000-6753.tces.191064.
10	余思贤, 周允康, 刘雷伟, 等. 海上风电-水下压缩空气储能系统建模及经济性分析[J]. 综合智慧能源, 2022, 44(10): 71-82.
	YU S X, ZHOU Y K, LIU L W, et al. Modeling and economic benefit analysis of an offshore wind power-underwater compressed air energy storage system[J]. Integrated Intelligent Energy, 2022, 44(10): 71-82.
11	LE H T, SANTOSO S, NGUYEN T Q. Augmenting wind power penetration and grid voltage stability limits using ESS: Application design, sizing, and a case study[J]. IEEE Transactions on Power Systems, 2012, 27(1): 161-171. DOI: 10.1109/TPWRS. 2011. 2165302.
12	DENHOLM P, SIOSHANSI R. The value of compressed air energy storage with wind in transmission-constrained electric power systems, Energy Policy 37 (8) (2009) 3149–3158.
13	应飞祥, 姜燕波, 何民, 等. 含风储系统的电力系统可靠性评估进展与展望[J]. 智慧电力, 2019, 47(2): 1-8, 42. DOI: 10.3969/j.issn.1673-7598.2019.02.001.
	YING F X, JIANG Y B, HE M, et al. Progress and prospect of reliability assessment of power system with wind farm and energy storage system[J]. Smart Power, 2019, 47(2): 1-8, 42. DOI: 10.3969/j.issn.1673-7598.2019.02.001.
14	谢开贵, 王岸, 胡博. 计及储能设备运行策略的风/柴/储混合系统可靠性评估[J]. 电力系统保护与控制, 2012, 40(9): 1-7. DOI: 10.3969/j.issn.1674-3415.2012.09.001.
	XIE K G, WANG A, HU B. Reliability evaluation of wind-diesel-storage hybrid system considering energy storage system operating strategies[J]. Power System Protection and Control, 2012, 40(9): 1-7. DOI: 10.3969/j.issn.1674-3415.2012.09.001.
15	BAGEN B, BILLINTON R. Reliability cost/worth associated with wind energy and energy storage utilization in electric power systems[C]//Proceedings of the 10th International Conference on Probablistic, Methods Applied to Power Systems, 2008: 1-7.
16	GAO Z Y, WANG P, BERTLING L, et al. Sizing of energy storage for power systems with wind farms based on reliability cost and wroth analysis[C]//2011 IEEE Power and Energy Society General Meeting. July 24-28, 2011, Detroit, MI, USA. IEEE, 2011: 1-7. DOI: 10.1109/PES.2011.6039468.
17	刘畅, 卓建坤, 赵东明, 等. 利用储能系统实现可再生能源微电网灵活安全运行的研究综述[J]. 中国电机工程学报, 2020, 40(1): 1-18, 369. DOI: 10.13334/j.0258-8013.pcsee.190212.
	LIU C, ZHUO J K, ZHAO D M, et al. A review on the utilization of energy storage system for the flexible and safe operation of renewable energy microgrids[J]. Proceedings of the CSEE, 2020, 40(1): 1-18, 369. DOI: 10.13334/j.0258-8013.pcsee.190212.
18	CLEARY B, DUFFY A, OCONNOR A, et al. Assessing the economic benefits of compressed air energy storage for mitigating wind curtailment[J]. IEEE Transactions on Sustainable Energy, 2015, 6(3): 1021-1028. DOI: 10.1109/TSTE. 2014. 2376698.
19	TIAN Y T, BERA A, BENIDRIS M, et al. Reliability and environmental benefits of energy storage systems in firming up wind generation[C]//2017 North American Power Symposium (NAPS). September 17-19, 2017, Morgantown, WV, USA. IEEE, 2017: 1-6. DOI: 10.1109/NAPS.2017.8107315.
20	李强, 王璇, 琚诚, 等. 基于广义储能的多时间尺度综合能源系统优化调度模型[J/OL]. 南方电网技术, 2023 [2023-11-21]. https://kns.cnki.net/kcms/detail/44.1643.TK.20231120.1054.002.html.
21	DHUNGANA D, KARKI R. Data constrained adequacy assessment for wind resource planning[J]. IEEE Transactions on Sustainable Energy, 2015, 6(1): 219-227. DOI: 10.1109/TSTE. 2014.2364778.
22	GIORSETTO P, UTSUROGI K F. Development of a new procedure for reliability modeling of wind turbine generators[J]. IEEE Transactions on Power Apparatus and Systems, 1983, PAS-102(1): 134-143. DOI: 10.1109/TPAS.1983.318006.
23	BEHRENDT L. Taxes and incentives for renewable energy[R]. KPMG 2017.
24	BILLINTON R, LI W Y. Reliability assessment of electric power systems using Monte Carlo Methods[M]. Boston, MASpringer US, 1994, DOI: 10.1007/978-1-4899-1346-3.
25	SIOSHANSI R, MADAENI S H, DENHOLM P. A dynamic programming approach to estimate the capacity value of energy storage[J]. IEEE Transactions on Power Systems, 2014, 29(1): 395-403. DOI: 10.1109/TPWRS.2013.2279839.
26	SUBCOMMITTEE P M. IEEE reliability test system[J]. IEEE Transactions on Power Apparatus and Systems, 1979, PAS-98(6): 2047-2054. DOI: 10.1109/TPAS.1979.319398.
27	LUO X, WANG J, DOONER M, CLARKE J. Overview of current development in electrical energy storage technologies and the application potential in power system operation[J]. Appl Energy, 2015, 137(17): 511-536.
28	AESOPoolPrice. Market and system reporting [J/OL]. [2024-05-01] http://ets.aeso.ca/ ets_web/ docroot/ Market/ Reports/ Historical ReportsStart.html.
29	张家俊, 李晓琼, 张振涛,等. 压缩二氧化碳储能系统研究进展[J]. 储能科学与技术, 2023, 12(6): 1928-1945.
	ZHANG J J, LI X Q, ZHANG Z T, et al. Research progress of compressed carbon dioxide energy storage system[J]. Energy Storage Science and Technology, 2023, 12(6): 1928-1945.
30	XU Y X, SINGH C. Adequacy and economy analysis of distribution systems integrated with electric energy storage and renewable energy resources[J]. IEEE Transactions on Power Systems, 2012, 27(4): 2332-2341. DOI: 10.1109/TPWRS. 2012. 2186830.
31	李杨. 压缩空气储能储气库热力学改进的数学模型[J]. 储能科学与技术, 2024, 13(5): 1707-1709.
	LI Y. Mathematical model of thermodynamic improvement of compressed air storage gas storage[J]. Energy Storage Science and Technology, 2024, 13(5): 1707-1709.
32	陈海生, 李泓, 徐玉杰, 等. 2023年中国储能技术研究进展[J]. 储能科学与技术, 2024, 13(5): 1359-1397.
	CHEN H S, LI H, XU Y J, et al. Research progress on energy storage technologies of China in 2023[J]. Energy Storage Science and Technology, 2024, 13(5): 1359-1397.

时间	停电时间成本/(CNY/kW)
1 min	1.41
30 min	3.28
1 h	8.86
10 h	80.56
24 h	137.8

场景	负荷预期损失/(h/年)	预期缺电量 /(MWh/年)	未使用能源的成本/10000亿	容量值/MW	预期风能供应/(GWh/年)
1	8.241	4.23	4.27	4.61	3.87
2	1274	501	531	543	455
3	8.54	3.97	4.68	4.75	4.14
4		135	124	115	127
5		1087	1087	886	996

[1]	栗占伟, 樊东方, 曾超, 何雯倩, 何金. 考虑风光消纳的储能系统容量优化配置及运行策略研究[J]. 储能科学与技术, 2024, 13(8): 2713-2725.
[2]	李澎煜, 林曦鹏, 王亮, 陈海生, 王艺斐. 竖直波纹流道内超临界氮气流动与传热研究[J]. 储能科学与技术, 2024, 13(8): 2605-2614.
[3]	李永奇, 杜蕴, 方振华, 张松通, 祝夏雨, 胡海良, 邱景义, 明海. 军用新能源微电网系统的运维及故障处置分析[J]. 储能科学与技术, 2024, 13(8): 2740-2757.
[4]	赵全胜, 朱玲, 刘尧伍, 郝军刚, 武明鑫. 压缩空气储能电站浅埋人工储气洞库设计基本理念和方法[J]. 储能科学与技术, 2024, 13(8): 2775-2784.
[5]	韩汶昕, 张雪辉, 许剑, 傅力宏, 蒋鑫, 郭文宾, 谢宇超, 陈海生. 压气机叶顶间隙流动与控制研究进展[J]. 储能科学与技术, 2024, 13(6): 1940-1962.
[6]	甄箫斐, 王贝贝, 张小虎, 孙一铭, 曹文炅, 董缇. 锂电池储能系统热失控气体生成及扩散规律研究[J]. 储能科学与技术, 2024, 13(6): 1986-1994.
[7]	郭祚刚, 刘通, 徐敏, 徐申, 陈光明, 郝新月. 新型喷射增效压缩空气储能系统性能[J]. 储能科学与技术, 2024, 13(6): 1877-1887.
[8]	张大兴, 黄泽荣, 王祥东, 王延凯, 蔡冰子, 袁昊宇, 田明明, 袁英平, 曹原. 基于功率变换器的梯次利用电池系统均衡控制策略[J]. 储能科学与技术, 2024, 13(5): 1635-1642.
[9]	李润源, 郭傅傲, 赵钢超. 集装箱式锂离子电池储能系统消防安全早期预警方法[J]. 储能科学与技术, 2024, 13(5): 1595-1602.
[10]	张研, 袁征. 压缩空气储能系统的微机电控制技术[J]. 储能科学与技术, 2024, 13(5): 1551-1553.
[11]	李杨. 压缩空气储能储气库热力学改进的数学模型[J]. 储能科学与技术, 2024, 13(5): 1707-1709.
[12]	张杰, 吴成辉, 潘明俊, 赵天恩. 电池储能系统绝缘电阻检测方法误差分析[J]. 储能科学与技术, 2024, 13(4): 1167-1175.
[13]	张金亚, 周文博, 程紫漪漪. 基于LBM的泡沫金属与翅片相变储能系统性能对比分析[J]. 储能科学与技术, 2024, 13(2): 598-607.
[14]	张留淦, 周颖驰, 孙文兵, 叶楷, 陈龙祥. 利用ORC-VCR回收压缩热的预冷式CAES系统性能分析[J]. 储能科学与技术, 2024, 13(2): 611-622.
[15]	刘洋恺, 孙伟卿, 刘唯. 基于AHP和TOPSIS-模糊综合评价的多场景储能选型方法[J]. 储能科学与技术, 2024, 13(2): 691-701.