综合能源系统下虚拟储能建模方法与应用场景研究综述及展望

doi:10.11930/j.issn.1004-9649.202311066

中国电力 ›› 2024, Vol. 57 ›› Issue (6): 53-68.DOI: 10.11930/j.issn.1004-9649.202311066

• 新型电力系统储能规划与运行关键技术 • 上一篇下一篇

综合能源系统下虚拟储能建模方法与应用场景研究综述及展望

苏娟(), 李拓(), 刘峻玮, 夏越(), 杜松怀

中国农业大学信息与电气工程学院，北京　100083

收稿日期:2023-11-15 接受日期:2024-04-03 出版日期:2024-06-28 发布日期:2024-06-25
作者简介:苏娟（1980—），女，博士，副教授，从事电力市场、综合能源系统优化运行、电力需求侧管理等研究，E-mail：sujuan@cau.edu.cn
李拓（1998—），男，硕士研究生，从事综合能源系统优化运行研究，E-mail：18956175502@163.com
夏越（1988—），男，博士，通信作者，副教授，从事电力系统建模与仿真、综合能源系统动态建模与仿真方面研究，E-mail：xiayuexiayue@163.com
基金资助:
国家自然科学基金资助项目（基于移频理论的电/热/气多能源系统多时间尺度暂态建模和多速率仿真方法研究，52007194）。

Review and Prospect of Modeling Method and Application Scenarios of Virtual Energy Storage under Integrated Energy System

Juan SU(), Tuo LI(), Junwei LIU, Yue XIA(), Songhuai DU

College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China

Received:2023-11-15 Accepted:2024-04-03 Online:2024-06-28 Published:2024-06-25
Supported by:
This work is supported by National Natural Science Foundation of China (Research on Multi-time Scale Transient Modeling and Multi-rate Simulation Method of Electric/Thermal/Gas Multi-energy System Based on Frequency Shift Theory, No.52007194).

摘要/Abstract

摘要：

为了促进多能耦合互补和实现可再生能源就地消纳，综合能源系统已成为多领域的研究热点。考虑到能源设备及网络的多样性、复杂性以及多种能源时间尺度的差异性，根据能量平衡原理，对系统内具有可调特性的源、网、荷进行储能化建模，并构成虚拟储能系统参与到综合能源系统的优化调度中。为了准确把握虚拟储能的研究重点，首先介绍了虚拟储能的定义、逻辑架构和技术内涵；其次针对综合能源系统源、网、荷端设备或网络，总结和归纳了4种虚拟储能建模方法和特性指标；然后重点分析了虚拟储能在4种典型场景的具体应用；最后展望了虚拟储能未来的发展方向。

关键词: 综合能源系统, 虚拟储能, 建模方法, 应用场景

Abstract:

In order to facilitate the complementary coupling of various forms of energy and achieve local consumption of renewable energy, integrated energy system (IES) has become a research hotspot across multiple disciplines. Considering the diversity and complexity of energy devices and networks, as well as the disparity in energy time scales, the source, grid and load with adjustable characteristics within the system are modeled as storage elements using energy balance principles, and a virtual energy storage system is constructed with them, which is incorporated into the optimization and scheduling of the IES. To accurately grasp the research focus of virtual energy storage, this paper firstly introduces the definition, logical structure and technical connotation of virtual energy storage, and summarizes four virtual energy storage modeling methods and characteristic indexes for the equipment or network on the source, grid and load side of integrated energy system, and then emphatically analyzes the specific application of virtual energy storage in four typical scenarios, and finally looks ahead to the future development direction of virtual energy storage.

Key words: integrated energy system, virtual energy storage, modeling method, application scenario

苏娟, 李拓, 刘峻玮, 夏越, 杜松怀. 综合能源系统下虚拟储能建模方法与应用场景研究综述及展望[J]. 中国电力, 2024, 57(6): 53-68.

Juan SU, Tuo LI, Junwei LIU, Yue XIA, Songhuai DU. Review and Prospect of Modeling Method and Application Scenarios of Virtual Energy Storage under Integrated Energy System[J]. Electric Power, 2024, 57(6): 53-68.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202311066

https://www.electricpower.com.cn/CN/Y2024/V57/I6/53

图/表 5

参考文献 69

1	陈国平, 梁志峰, 董昱. 基于能源转型的中国特色电力市场建设的分析与思考[J]. 中国电机工程学报, 2020, 40 (2): 369- 379.
	CHEN Guoping, LIANG Zhifeng, DONG Yu. Analysis and reflection on the marketization construction of electric power with Chinese characteristics based on energy transformation[J]. Proceedings of the CSEE, 2020, 40 (2): 369- 379.
2	国家能源局. 国家能源局2023年一季度新闻发布会文字实录[EB/OL]. (2023-02-13)[2023-11-11]. http://www.nea.gov.cn/2023-02/13/c_1310697149.htm.
3	GUERRA K, HARO P, GUTIÉRREZ R E, et al. Facing the high share of variable renewable energy in the power system: flexibility and stability requirements[J]. Applied Energy, 2022, 310, 118561.
4	黎静华, 朱梦姝, 陆悦江, 等. 综合能源系统优化调度综述[J]. 电网技术, 2021, 45 (6): 2256- 2272.
	LI Jinghua, ZHU Mengshu, LU Yuejiang, et al. Review on optimal scheduling of integrated energy systems[J]. Power System Technology, 2021, 45 (6): 2256- 2272.
5	孙伟卿, 向威, 裴亮, 等. 电力辅助服务市场下的用户侧广义储能控制策略[J]. 电力系统自动化, 2020, 44 (2): 68- 76.
	SUN Weiqing, XIANG Wei, PEI Liang, et al. Generalized energy storage control strategies on user side in power ancillary service market[J]. Automation of Electric Power Systems, 2020, 44 (2): 68- 76.
6	HAMZEH A F, WIJESOORIYA M M, BEHNAM M I, et al. Optimal scheduling of multi-energy type virtual energy storage system in reconfigurable distribution networks for congestion management[J]. Applied Energy, 2023, 333, 120569.
7	钟雅珊, 付聪, 钱峰, 等. 考虑广义储能和条件风险价值的综合能源系统经济调度[J]. 电力系统保护与控制, 2022, 50 (9): 54- 63.
	ZHONG Yashan, FU Cong, QIAN Feng, et al. Economic dispatch model of an integrated energy system considering generalized energy storage and conditional value at risk[J]. Power System Protection and Control, 2022, 50 (9): 54- 63.
8	AMINI M, ALMASSALKHI M. Optimal corrective dispatch of uncertain virtual energy storage systems[J]. IEEE Transactions on Smart Grid, 2020, 11 (5): 4155- 4166.
9	XIE K, HUI H X, DING Y. Review of modeling and control strategy of thermostatically controlled loads for virtual energy storage system[J]. Protection and Control of Modern Power Systems, 2019, 4 (1): 23.
10	孙毅, 李泽坤, 许鹏, 等. 异构柔性负荷建模调控关键技术及发展方向研究[J]. 中国电机工程学报, 2019, 39 (24): 7146- 7158, 7488.
	SUN Yi, LI Zekun, XU Peng, et al. Research on key technologies and development direction of heterogeneous flexible load modeling and regulation[J]. Proceedings of the CSEE, 2019, 39 (24): 7146- 7158, 7488.
11	李力, 董密, 宋冬然, 等. 分布式的温控负荷集群负荷跟随控制[J/OL]. 中国电机工程学报, 2022: 1–13. (2022-12-16).https://kns.cnki.net/kcms/detail/11.2107.TM.20221215.1555.003.html.
	LI Li, DONG Mi, SONG Dongran, et al. Distributed load-following control for thermostatically controlled loads clusters[J/OL]. Proceedings of the CSEE, 2022: 1–13. (2022-12-16).https://kns.cnki.net/kcms/detail/11.2107.TM.20221215.1555.003.html.
12	KANG W F, CHEN M Y, LAI W, et al. Distributed real-time power management for virtual energy storage systems using dynamic price[J]. Energy, 2021, 216, 119069.
13	汤木易, 罗毅, 胡博, 等. 电热联合调度模型综述[J]. 电力系统保护与控制, 2020, 48 (23): 161- 175.
	TANG Muyi, LUO Yi, HU Bo, et al. A review of the dispatch model of a combined heat and power system[J]. Power System Protection and Control, 2020, 48 (23): 161- 175.
14	梁馨予. 考虑虚拟储能的区域综合能源系统运行优化研究[D]. 南京: 东南大学, 2021.
	LIANG Xinyu. Research on optimal operation of regional integrated energy system considering virtual energy Storage[D]. Nanjing: Southeast University, 2021.
15	MENG K, DONG Z Y, XU Z, et al. Coordinated dispatch of virtual energy storage systems in smart distribution networks for loading management[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 49(4): 776–786.
16	高文浩, 赵海兵, 殷爽睿, 等. 考虑负荷虚拟储能特性的商业区储能优化配置[J]. 中国电力, 2020, 53 (4): 96- 104.
	GAO Wenhao, ZHAO Haibing, YIN Shuangrui, et al. Optimal configuration of BESS in commercial area considering virtual energy storage characteristics of load[J]. Electric Power, 2020, 53 (4): 96- 104.
17	王怡岚, 童亦斌, 黄梅, 等. 基于需求侧响应的空调负荷虚拟储能模型研究[J]. 电网技术, 2017, 41 (2): 394- 401.
	WANG Yilan, TONG Yibin, HUANG Mei, et al. Research on virtual energy storage model of air conditioning loads based on demand response[J]. Power System Technology, 2017, 41 (2): 394- 401.
18	VIJAYALAKSHMI K, VIJAYAKUMAR K, NANDHAKUMAR K. Prediction of virtual energy storage capacity of the air-conditioner using a stochastic gradient descent based artificial neural network[J]. Electric Power Systems Research, 2022, 208, 107879.
19	VIJAYALAKSHMI K, VIJAYAKUMAR K, NANDHAKUMAR K. An ensemble learning model for estimating the virtual energy storage capacity of aggregated air-conditioners[J]. Journal of Energy Storage, 2023, 59, 106512.
20	殷爽睿, 艾芊, 王大鹏, 等. 考虑空调负荷虚拟储能的产消者鲁棒日前申报策略[J]. 电力系统自动化, 2020, 44 (4): 24- 34.
	YIN Shuangrui, AI Qian, WANG Dapeng, et al. Day-ahead robust bidding strategy for prosumer considering virtual energy storage of air-conditioning load[J]. Automation of Electric Power Systems, 2020, 44 (4): 24- 34.
21	WANG D X, MENG K, GAO X D, et al. Coordinated dispatch of virtual energy storage systems in LV grids for voltage regulation[J]. IEEE Transactions on Industrial Informatics, 2018, 14 (6): 2452- 2462.
22	WANG D, LAI C S, LI X, et al. Smart coordination of virtual energy storage systems for distribution network management[J]. International Journal of Electrical Power and Energy Systems, 2021, 129 (4): 106816.
23	靳小龙, 穆云飞, 贾宏杰, 等. 集成智能楼宇的微网系统多时间尺度模型预测调度方法[J]. 电力系统自动化, 2019, 43 (16): 25- 33.
	JIN Xiaolong, MU Yunfei, JIA Hongjie, et al. Model predictive control based multiple-time-scheduling method for microgrid system with smart buildings integrated[J]. Automation of Electric Power Systems, 2019, 43 (16): 25- 33.
24	朱佳男, 艾芊, 李嘉媚. 基于分布鲁棒优化的广义共享储能容量配置方法[J/OL]. 电力系统自动化, 1–11(2023-11-23).https://link.cnki.net/urlid/32.1180.TP.20231122.1036.006.
	ZHU Jianan, AI Qian, LI Jiamei. Allocation method of generalized shared energy storage capacity based on distributed robust optimization[J/OL]. Automation of Electric Power Systems: 1–11(2023-11-23).https://link.cnki.net/urlid/32.1180.TP.20231122.1036.006.
25	SONG M, GAO C W, YAN H G, et al. Thermal battery modeling of inverter air conditioning for demand response[J]. IEEE Transactions on Smart Grid, 2018, 9 (6): 5522- 5534.
26	王剑晓, 钟海旺, 夏清, 等. 基于成本—效益分析的温控负荷需求响应模型与方法[J]. 电力系统自动化, 2016, 40 (5): 45- 53.
	WANG Jianxiao, ZHONG Haiwang, XIA Qing, et al. Model and method of demand response for thermostatically-controlled loads based on cost-benefit analysis[J]. Automation of Electric Power Systems, 2016, 40 (5): 45- 53.
27	栗子豪, 李铁, 吴文传, 等. 基于Minkowski Sum的热泵负荷调度灵活性聚合方法[J]. 电力系统自动化, 2019, 43 (5): 14- 21.
	LI Zihao, LI Tie, WU Wenchuan, et al. Minkowski sum based flexibility aggregating method of load dispatching for heat pumps[J]. Automation of Electric Power Systems, 2019, 43 (5): 14- 21.
28	王冉, 王丹, 贾宏杰, 等. 一种平抑微网联络线功率波动的电池及虚拟储能协调控制策略[J]. 中国电机工程学报, 2015, 35 (20): 5124- 5134.
	WANG Ran, WANG Dan, JIA Hongjie, et al. A coordination control strategy of battery and virtual energy storage to smooth the micro-grid tie-line power fluctuations[J]. Proceedings of the CSEE, 2015, 35 (20): 5124- 5134.
29	CHENG M, SAMI S S, WU J Z. Benefits of using virtual energy storage system for power system frequency response[J]. Applied Energy, 2017, 194, 376- 385.
30	KUMAR K N, VIJAYAKUMAR K, KALPESH C. Virtual energy storage capacity estimation using ANN-based kWh modelling of refrigerators[J]. IET Smart Grid, 2018, 1 (2): 31- 39.
31	刘翕铭, 于永进, 杨洋. 基于改进麻雀算法的园区综合能源系统优化研究[J]. 智慧电力, 2021, 49 (6): 9- 16,82.
	LIU Ximing, YU Yongjin, YANG Yang. Optimization of regional integrated energy system based on improved sparrow algorithm[J]. Smart Power, 2021, 49 (6): 9- 16,82.
32	戚野白, 王丹, 贾宏杰, 等. 基于需求响应的集群温控负荷建模及参与低频减载策略研究[J]. 中国电机工程学报, 2017, 37 (3): 751- 759.
	QI Yebai, WANG Dan, JIA Hongjie, et al. Research on under frequency load shedding strategy using aggregated thermostatically controlled loads based on demand response[J]. Proceedings of the CSEE, 2017, 37 (3): 751- 759.
33	崔杨, 周慧娟, 仲悟之, 等. 考虑广义储能与火电联合调峰的日前–日内两阶段滚动优化调度[J]. 电网技术, 2021, 45 (1): 10- 20.
	CUI Yang, ZHOU Huijuan, ZHONG Wuzhi, et al. Two-stage day-ahead and intra-day rolling optimization scheduling considering joint peak regulation of generalized energy storage and thermal power[J]. Power System Technology, 2021, 45 (1): 10- 20.
34	张祥宇, 舒一楠, 付媛. 基于虚拟储能的直流微电网源荷储多时间尺度能量优化与分区协调控制[J]. 电工技术学报, 2022, 37 (23): 6011- 6024.
	ZHANG Xiangyu, SHU Yinan, FU Yuan. Multi-time-scale energy optimization and zone coordinated control of DC microgrid source-load-storage based on virtual energy storage[J]. Transactions of China Electrotechnical Society, 2022, 37 (23): 6011- 6024.
35	张祥宇, 舒一楠, 付媛, 等. 含虚拟储能直流微电网的源荷储能量协同优化控制[J]. 高电压技术, 2023, 49 (8): 3497- 3506.
	ZHANG Xiangyu, SHU Yinan, FU Yuan, et al. Cooperative optimal control of source-load-storage energy in DC microgrid with virtual energy storage[J]. High Voltage Engineering, 2023, 49 (8): 3497- 3506.
36	朱旭, 杨军, 李高俊杰, 等. 计及虚拟储能系统的区域综合能源系统优化调度策略[J]. 电力建设, 2020, 41 (8): 99- 110.
	ZHU Xu, YANG Jun, LI Gaojunjie, et al. Optimal dispatching strategy of regional integrated energy system considering virtual energy storage system[J]. Electric Power Construction, 2020, 41 (8): 99- 110.
37	湛归, 殷爽睿, 艾芊, 等. 智能楼宇型虚拟电厂参与电力系统调频辅助服务策略[J]. 电力工程技术, 2022, 41 (6): 13- 20, 57.
	ZHAN Gui, YIN Shuangrui, AI Qian, et al. A strategy for smart building-based virtual power plants participating in frequency regulation auxiliary service[J]. Electric Power Engineering Technology, 2022, 41 (6): 13- 20, 57.
38	ZHU X, YANG J, LIU Y, et al. Optimal scheduling method for a regional integrated energy system considering joint virtual energy storage[J]. IEEE Access, 2019, 7, 138260- 138272.
39	李蓓, 赵松, 谢志佳, 等. 电动汽车虚拟储能可用容量建模[J]. 山东大学学报(工学版), 2020, 50 (6): 101- 111.
	LI Bei, ZHAO Song, XIE Zhijia, et al. Electric vehicle virtual energy storage available capacity modeling[J]. Journal of Shandong University (Engineering Science), 2020, 50 (6): 101- 111.
40	郭建府, 赵松, 韩晓娟. 基于冗余配置的电动汽车虚拟储能参与电网调峰研究[J]. 热力发电, 2020, 49 (8): 162- 168.
	GUO Jianfu, ZHAO Song, HAN Xiaojuan. Research on electric vehicles virtual energy storage based on redundant configuration participating in power grid peak shaving[J]. Thermal Power Generation, 2020, 49 (8): 162- 168.
41	朱兰, 刘伸, 唐陇军, 等. 充放电不确定性响应建模与电动汽车代理商日前调度策略[J]. 电网技术, 2018, 42 (10): 3305- 3317.
	ZHU Lan, LIU Shen, TANG Longjun, et al. Modeling of charging and discharging uncertainty and research on day-ahead dispatching strategy of electric vehicle agents[J]. Power System Technology, 2018, 42 (10): 3305- 3317.
42	张建宏, 赵兴勇, 王秀丽. 考虑奖励机制的电动汽车充电优化引导策略[J]. 电网与清洁能源, 2024, 40 (1): 102- 108, 118.
	ZHANG Jianhong, ZHAO Xingyong, WANG Xiuli. An optimization guidance strategy for electric vehicle charging considering the reward mechanism[J]. Power System and Clean Energy, 2024, 40 (1): 102- 108, 118.
43	李飞, 梁宝全, 张旭东, 等. 面向电动汽车快充站服务效率的自适应动态激励机制[J]. 电力自动化设备, 2022, 42 (2): 48- 55.
	LI Fei, LIANG Baoquan, ZHANG Xudong, et al. Adaptive dynamic incentive mechanism for service efficiency of EV fast charging station[J]. Electric Power Automation Equipment, 2022, 42 (2): 48- 55.
44	杨镜司, 秦文萍, 史文龙, 等. 基于电动汽车参与调峰定价策略的区域电网两阶段优化调度[J]. 电工技术学报, 2022, 37 (1): 58- 71.
	YANG Jingsi, QIN Wenping, SHI Wenlong, et al. Two-stage optimal dispatching of regional power grid based on electric vehicles' participation in peak-shaving pricing strategy[J]. Transactions of China Electrotechnical Society, 2022, 37 (1): 58- 71.
45	张祥宇, 吴奇, 付媛. 含虚拟储能直流微电网的储荷协调控制技术[J]. 电力自动化设备, 2021, 41 (1): 113- 120.
	ZHANG Xiangyu, WU Qi, FU Yuan. Coordinated control technology of energy storage-load for DC microgrid with virtual energy storage[J]. Electric Power Automation Equipment, 2021, 41 (1): 113- 120.
46	穆云飞, 唐志鹏, 吴志军, 等. 计及虚拟储能的电-水-热综合能源系统日前优化调度方法[J/OL]. 电力系统自动化, 2023: 1–16. (2023-06-30).https://kns.cnki.net/kcms/detail/32.1180.TP.20230629.1528.002.html.
	MU Yunfei, TANG Zhipeng, WU Zhijun, et al. Optimal day-ahead scheduling method for electricity water hot water integrated energy system considering virtual energy storage[J/OL]. Automation of Electric Power Systems, 2023: 1–16. (2023-06-30).https://kns.cnki.net/kcms/detail/32.1180.TP.20230629.1528.002.html.
47	邓拓宇, 田亮, 刘吉臻. 供热机组锅炉储能与热网储能空间时间多尺度分析[J]. 中国电机工程学报, 2017, 37 (2): 599- 606.
	DENG Tuoyu, TIAN Liang, LIU Jizhen. Spatial and temporal multiscale analysis on energy storage in heat supply units' boiler and heat supply nets[J]. Proceedings of the CSEE, 2017, 37 (2): 599- 606.
48	王楠, 张辰, 何旭道, 等. 基于弃风消纳的热网主动储热优化[J]. 中国电力, 2023, 56 (2): 114- 122.
	WANG Nan, ZHANG Chen, HE Xudao, et al. Optimization of active heat storage in heat-supply network considering curtailed wind power consumption[J]. Electric Power, 2023, 56 (2): 114- 122.
49	陈乾, 张沈习, 程浩忠, 等. 计及热网蓄热特性的多区域综合能源系统多元储能规划[J]. 中国电机工程学报, 2023, 43 (15): 5890- 5902.
	CHEN Qian, ZHANG Shenxi, CHENG Haozhong, et al. Multiple energy storage planning of multi-district integrated energy system considering heat storage characteristics of heat network[J]. Proceedings of the CSEE, 2023, 43 (15): 5890- 5902.
50	曾艾东, 王佳伟, 邹宇航, 等. 考虑供热管网储热的综合能源系统多时间尺度优化调度[J/OL]. 高电压技术: 1–13(2023-04-27).https://doi.org/10.13336/j.1003-6520.hve.20222086.
	ZENG Aidong, WANG Jiawei, ZOU Yuhang, et al. Multi-time-scale optimal scheduling of integrated energy system considering heat storage characteristics of heating network[J/OL]. High Voltage Engineering: 1–13(2023-04-27).https://doi.org/10.13336/j.1003-6520.hve.20222086.
51	栗海润, 穆云飞, 贾宏杰, 等. 考虑量化储热的多区域电–热综合能源系统优化调度[J]. 中国电机工程学报, 2021, 41 (S1): 16- 27.
	LI Hairun, MU Yunfei, JIA Hongjie, et al. Optimal scheduling of multiregional integrated power and heating system considering quantified thermal storage[J]. Proceedings of the CSEE, 2021, 41 (S1): 16- 27.
52	徐业琰, 彭思成, 廖清芬, 等. 考虑用户互补聚合响应与热能传输延时的综合能源园区运营商两阶段短期优化调度[J]. 电力自动化设备, 2017, 37 (6): 152- 163.
	XU Yeyan, PENG Sicheng, LIAO Qingfen, et al. Two-stage short-term optimal dispatch of MEP considering CAUR and HTTD[J]. Electric Power Automation Equipment, 2017, 37 (6): 152- 163.
53	XU F, HAO L, CHEN L, et al. Integrated heat and power optimal dispatch method considering the district heating networks flow rate regulation for wind power accommodation[J]. Energy, 2023, 263, 125656.
54	杨秀, 汤金璋, 刘方, 等. 流量自适应方式下考虑热管道虚拟储能的电热能源系统优化调度[J]. 中国电机工程学报, 2023, 43 (21): 8318- 8332.
	YANG Xiu, TANG Jinzhang, LIU Fang, et al. Optimal scheduling of electrothermal integrated energy system considering virtual energy storage of thermal pipelines in flow adaptive mode[J]. Proceedings of the CSEE, 2023, 43 (21): 8318- 8332.
55	JIN X L, WU J Z, MU Y F, et al. Hierarchical microgrid energy management in an office building[J]. Applied Energy, 2017, 208, 480- 494.
56	KOUHIA M, LAUKKANEN T, HOLMBERG H, et al. District heat network as a short-term energy storage[J]. Energy, 2019, 177, 293- 303.
57	王明军, 穆云飞, 孟宪君, 等. 考虑热能输运动态特性的电–热综合能源系统优化调度方法[J]. 电网技术, 2020, 44 (1): 132- 142.
	WANG Mingjun, MU Yunfei, MENG Xianjun, et al. Optimal scheduling method for integrated electro-thermal energy system considering heat transmission dynamic characteristics[J]. Power System Technology, 2020, 44 (1): 132- 142.
58	靳小龙, 穆云飞, 贾宏杰, 等. 融合需求侧虚拟储能系统的冷热电联供楼宇微网优化调度方法[J]. 中国电机工程学报, 2017, 37 (2): 581- 591.
	JIN Xiaolong, MU Yunfei, JIA Hongjie, et al. Optimal scheduling method for a combined cooling, heating and power building microgrid considering virtual storage system at demand side[J]. Proceedings of the CSEE, 2017, 37 (2): 581- 591.
59	张磊, 罗毅, 罗恒恒, 等. 基于集中供热系统储热特性的热电联产机组多时间尺度灵活性协调调度[J]. 中国电机工程学报, 2018, 38 (4): 985- 998, 1275.
	ZHANG Lei, LUO Yi, LUO Hengheng, et al. Scheduling of integrated heat and power system considering multiple time-scale flexibility of CHP unit based on heat characteristic of DHS[J]. Proceedings of the CSEE, 2018, 38 (4): 985- 998, 1275.
60	孙鹏, 滕云, 冷欧阳, 等. 考虑供热系统多重热惯性的电热联合系统协调优化[J]. 中国电机工程学报, 2020, 40 (19): 6059- 6071.
	SUN Peng, TENG Yun, LENG Ouyang, et al. Coordinated optimization of combined heat and power systems considering multiple thermal inertia of heating system[J]. Proceedings of the CSEE, 2020, 40 (19): 6059- 6071.
61	杜丽佳, 靳小龙, 何伟, 等. 考虑电动汽车和虚拟储能系统优化调度的楼宇微网联络线功率平滑控制方法[J]. 电力建设, 2019, 40 (8): 26- 33. DOI
	DU Lijia, JIN Xiaolong, HE Wei, et al. A tie-line power smoothing control method for an office building microgrid by scheduling thermal mass of the building and plug-in electric vehicles[J]. Electric Power Construction, 2019, 40 (8): 26- 33. DOI
62	艾欣, 赵阅群, 周树鹏. 空调负荷直接负荷控制虚拟储能特性研究[J]. 中国电机工程学报, 2016, 36 (6): 1596- 1603.
	AI Xin, ZHAO Yuequn, ZHOU Shupeng. Study on virtual energy storage features of air conditioning load direct load control[J]. Proceedings of the CSEE, 2016, 36 (6): 1596- 1603.
63	陈沼宇, 王丹, 贾宏杰, 等. 基于连续状态变量约束的微网虚拟储能系统最优平抑控制策略[J]. 电网技术, 2017, 41 (1): 55- 63.
	CHEN Zhaoyu, WANG Dan, JIA Hongjie, et al. Optimal smoothing control strategy of virtual energy storage system in microgrid based on continuous state constraints[J]. Power System Technology, 2017, 41 (1): 55- 63.
64	屠聪为, 曹军, 于东立, 等. 基于空调负荷的虚拟储能参与调频的控制策略[J]. 电力需求侧管理, 2019, 21 (1): 16- 21. DOI
	TU Congwei, CAO Jun, YU Dongli, et al. Control strategy of virtual energy storage system participating in frequency modulation based on air conditioning loads[J]. Power Demand Side Management, 2019, 21 (1): 16- 21. DOI
65	ZHENG Y, HILL D, LIU T, et al. Supplementary frequency regulation with multiple virtual energy storage system aggregators[J]. Electric Power Components and Systems, 2018, 46 (16/17): 1719- 1730.
66	蔡志宏, 吴杰康, 王瑞东, 等. 考虑空调群虚拟储能的配电网电压无功协同控制研究[J]. 电力需求侧管理, 2021, 23 (6): 63- 68. DOI
	CAI Zhihong, WU Jiekang, WANG Ruidong, et al. Coordinated control research for voltage and reactive power of distribution network considering virtual energy storage of air-conditionings[J]. Power Demand Side Management, 2021, 23 (6): 63- 68. DOI
67	WANG Y, TANG Y, XU Y, et al. A distributed control scheme of thermostatically controlled loads for the building-microgrid community[J]. IEEE Transactions on Sustainable Energy, 2020, 11 (1): 350- 360.
68	林俐, 顾嘉, 王钤. 面向风电消纳的考虑热网特性及热舒适度弹性的电热联合优化调度[J]. 电网技术, 2019, 43 (10): 3648- 3661.
	LIN Li, GU Jia, WANG Qian. Optimal dispatching of combined heat-power system considering characteristics of thermal network and thermal comfort elasticity for wind power accommodation[J]. Power System Technology, 2019, 43 (10): 3648- 3661.
69	杨丽君, 梁景志, 曹玉洁, 等. 基于热网储热特性的电-热系统联合经济调度[J]. 太阳能学报, 2020, 41 (5): 1- 8.
	YANG Lijun, LIANG Jingzhi, CAO Yujie, et al. Joint economic dispatch of power and heating supply system considering energy storage characteristics[J]. Acta Energiae Solaris Sinica, 2020, 41 (5): 1- 8.

负荷模型	模型精度	求解效率	模型适用性
微观动态模型	充分考虑了负荷受到各种因素影响时响应情况，精度较高	包含大量的变量和复杂的非线性方程，求解效率较低	适用于具有明显时变特性、快速响应以及包含复杂内部结构和交互关系的单一负荷分析；系统规模较小，所涉及负荷特性变化在同一时间尺度上
虚拟储能模型	通过等效参数替代的方法简化复杂的动态过程，但精度较低	仅需考虑能量的输入输出和储存等关键变量，动态方程线性化，求解效率较高	适用于需要实现能量平衡或灵活调度的场景；系统规模较大，所涉及的负荷特性变化具有较大的差异，无法在同一时间尺度上分析

负荷模型	模型精度	求解效率	模型适用性
微观动态模型	充分考虑了负荷受到各种因素影响时响应情况，精度较高	包含大量的变量和复杂的非线性方程，求解效率较低	适用于具有明显时变特性、快速响应以及包含复杂内部结构和交互关系的单一负荷分析；系统规模较小，所涉及负荷特性变化在同一时间尺度上
虚拟储能模型	通过等效参数替代的方法简化复杂的动态过程，但精度较低	仅需考虑能量的输入输出和储存等关键变量，动态方程线性化，求解效率较高	适用于需要实现能量平衡或灵活调度的场景；系统规模较大，所涉及的负荷特性变化具有较大的差异，无法在同一时间尺度上分析

虚拟储能类型	充放能功率	储能容量	充放能时间	荷能状态
实体储能	参与电力调度的可调节功率	由自身物理或化学储能特性决定	与设备参数有关	剩余电量与额定容量的比值
温控负荷	暂态功率与稳态功率的差值	取决于可调温度上下限	与体感温度变化速度有关	实时温度差与用户舒适度区间的比值
电动汽车	可参与需求响应量	取决于最大充电时长	与用户用能特性有关	剩余可响应量与最大可响应量的比值
旋转电机	可参与需求响应量	取决于转子转速上下限	与转子转动惯量有关	转子转速与额定转速的平方比
供热管网	受热源功率、管网热损耗和热负荷需求的影响	取决于供水温度上下限	与热媒温度变化速度有关	热媒温度与管道承受温度上下限的比值

虚拟储能类型	充放能功率	储能容量	充放能时间	荷能状态
实体储能	参与电力调度的可调节功率	由自身物理或化学储能特性决定	与设备参数有关	剩余电量与额定容量的比值
温控负荷	暂态功率与稳态功率的差值	取决于可调温度上下限	与体感温度变化速度有关	实时温度差与用户舒适度区间的比值
电动汽车	可参与需求响应量	取决于最大充电时长	与用户用能特性有关	剩余可响应量与最大可响应量的比值
旋转电机	可参与需求响应量	取决于转子转速上下限	与转子转动惯量有关	转子转速与额定转速的平方比
供热管网	受热源功率、管网热损耗和热负荷需求的影响	取决于供水温度上下限	与热媒温度变化速度有关	热媒温度与管道承受温度上下限的比值

[1]	周建华, 梁昌誉, 史林军, 李杨, 易文飞. 计及阶梯式碳交易机制的综合能源系统优化调度[J]. 中国电力, 2025, 58(2): 77-87.
[2]	张玉敏, 尹延宾, 吉兴全, 叶平峰, 孙东磊, 宋爱全. 计及热网不同运行状态下灵活性供给能力的综合能源系统优化调度[J]. 中国电力, 2025, 58(2): 88-102.
[3]	胡景成, 范耘豪, 朱同, 陈珍萍. 基于同态加密的综合能源系统完全分布式低碳经济调度[J]. 中国电力, 2025, 58(2): 164-175.
[4]	陆海, 张浩, 陈晓云, 周苏洋. 基于双层博弈的多能源网络协同规划方法[J]. 中国电力, 2025, 58(1): 93-99.
[5]	鲁玲, 苑涛, 杨波, 李欣, 鲁洋, 蒲秋平, 张鑫. 计及㶲效率和多重不确定性的区域综合能源系统双层优化[J]. 中国电力, 2025, 58(1): 128-140.
[6]	谭玲玲, 汤伟, 楚冬青, 李竞锐, 张玉敏, 吉兴全. 基于主从博弈的电热氢综合能源系统优化运行[J]. 中国电力, 2024, 57(9): 136-145.
[7]	高明非, 韩中合, 赵斌, 李鹏, 吴迪. 区域综合能源系统多类型储能协同优化与运行策略[J]. 中国电力, 2024, 57(9): 205-216.
[8]	卢纯颢, 周春丽, 林溪桥, 陈志君. 基于车辆行为模拟的加氢站氢负荷概率建模方法[J]. 中国电力, 2024, 57(8): 46-54, 66.
[9]	王辉, 周珂锐, 吴作辉, 邹智超, 李欣. 含电转气和碳捕集耦合的综合能源系统多时间尺度优化调度[J]. 中国电力, 2024, 57(8): 214-226.
[10]	景巍巍, 王强, 程好, 王博, 岳付昌, 王沉, 王文学. 电热综合能源系统稳态与区间潮流计算快速解耦新方法[J]. 中国电力, 2024, 57(7): 203-213.
[11]	陈兴龙, 曹喜民, 陈洁, 刘俊, 张育超, 包洪印. 绿证-碳交易机制下热电灵活响应的园区综合能源系统优化调度[J]. 中国电力, 2024, 57(6): 110-120.
[12]	胡福年, 张彭成, 周小博, 陈军. 计及灵活性资源的综合能源系统源荷协调优化调度[J]. 中国电力, 2024, 57(5): 2-13.
[13]	王云龙, 韩璐, 罗树林, 吴涛. 集成电动汽车的家庭电热综合能源系统负荷调度优化[J]. 中国电力, 2024, 57(5): 39-49.
[14]	李江南, 程韧俐, 周保荣, 刘稼瑾, 毛田, 赵文猛, 王滔, 黄光磊, 许银亮. 含碳捕集及电转氢设备的低碳园区综合能源系统随机优化调度[J]. 中国电力, 2024, 57(5): 149-156.
[15]	李梓萌, 王天阔, 胡鹏飞, 于彦雪, 杜翼, 蔡期塬. 基于能量枢纽的沼–风–光综合能源系统双层协同优化配置[J]. 中国电力, 2024, 57(4): 1-13.

综合能源系统下虚拟储能建模方法与应用场景研究综述及展望

Review and Prospect of Modeling Method and Application Scenarios of Virtual Energy Storage under Integrated Energy System

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献 69

相关文章 15

编辑推荐

Metrics

模态框（Modal）标题

综合能源系统下虚拟储能建模方法与应用场景研究综述及展望

Review and Prospect of Modeling Method and Application Scenarios of Virtual Energy Storage under Integrated Energy System

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献 69

相关文章 15

编辑推荐

Metrics