Aggregation and Operation Key Technology of Virtual Power Plant with Flexible Resources in Electricity Market Environment: Review

doi:10.11930/j.issn.1004-9649.202409025

Abstract

Abstract:

The rapid development and increasing number of flexible resource technologies offer immense potential for enhancing the flexibility and economic efficiency of power systems. Virtual power plants (VPPs) provide an effective means for supporting the participation of massive, heterogeneous, and decentralized resources in power market transactions through coordinated management and aggregated control of these resources. Addressing issues such as the difficulty in efficiently managing diverse and massive heterogeneous flexible resources within VPPs in the power market environment, benefit conflicts among different operating entities, and the coupling relationship between energy and ancillary services, this paper analyzes and summarizes the technical challenges, current research progress, and future research directions in the end-to-end operation of flexible resource VPPs in the power market environment. The analysis focuses on three aspects of flexible resource VPPs: aggregated modeling, bidding strategies, and operational control. It systematically summarizes the model characteristics, correlations, and applicable scenarios of relevant mainstream technological approaches. This comprehensive understanding of the key scientific issues, core theoretical methods, and mainstream technical solutions involved in flexible resource VPPs in the power market environment provides suggestions for future research directions and technological development of flexible resource VPPs.

Key words: electricity market, virtual power plant, distributed energy resource, aggregation, bidding strategy, operation control

Zhongkai YI, Langbo HOU, Ying XU, Yongfeng WU, Zhimin LI, Junfei WU, Teng FENG, Liu HAN. Aggregation and Operation Key Technology of Virtual Power Plant with Flexible Resources in Electricity Market Environment: Review[J]. Electric Power, 2024, 57(12): 82-96.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202409025

https://www.electricpower.com.cn/EN/Y2024/V57/I12/82

Figures/Tables 4

References 100

1	国家能源局. 进一步构建高质量充电基础设施体系, 更好满足人民群众购置和使用新能源汽车需要[EB/OL]. (2024-01-25) [2024-05-15]. https://www.nea.gov.cn/2024-01/25/c_1310762007.htm.
2	中国电力企业联合会. 中国电力行业年度发展报告2023[EB/OL]. (2023-08-07) [2024-05-15]. https://cec.org.cn/detail/index.html?3-322624.
3	HE G N, CHEN Q X, KANG C Q, et al. Optimal bidding strategy of battery storage in power markets considering performance-based regulation and battery cycle life[J]. IEEE Transactions on Smart Grid, 2015, 7 (5): 2359- 2367.
4	陈会来, 张海波, 王兆霖. 不同类型虚拟电厂市场及调度特性参数聚合算法研究综述[J]. 中国电机工程学报, 2023, 43 (1): 15- 28.
	CHEN Huilai, ZHANG Haibo, WANG Zhaolin. A review of market and scheduling characteristic parameter aggregation algorithm of different types of virtual power plants[J]. Proceedings of the CSEE, 2023, 43 (1): 15- 28.
5	CAMAL S, MICHIORRI A, KARINIOTAKIS G. Optimal offer of automatic frequency restoration reserve from a combined PV/wind virtual power plant[J]. IEEE Transactions on Power Systems, 2018, 33 (6): 6155- 6170. DOI
6	PONOĆKO J, MILANOVIĆ J V. Forecasting demand flexibility of aggregated residential load using smart meter data[J]. IEEE Transactions on Power Systems, 2018, 33 (5): 5446- 5455. DOI
7	王宣元, 刘蓁. 虚拟电厂参与电网调控与市场运营的发展与实践[J]. 电力系统自动化, 2022, 46 (18): 158- 168. DOI
	WANG Xuanyuan, LIU Zhen. Development and practice of virtual power plant participating in power grid regulation and market operation[J]. Automation of Electric Power Systems, 2022, 46 (18): 158- 168. DOI
8	殷爽睿, 艾芊, 宋平, 等. 虚拟电厂分层互动模式与可信交易框架研究与展望[J]. 电力系统自动化, 2022, 46 (18): 118- 128. DOI
	YIN Shuangrui, AI Qian, SONG Ping, et al. Research and prospect of hierarchical interaction mode and trusted transaction framework for virtual power plant[J]. Automation of Electric Power Systems, 2022, 46 (18): 118- 128. DOI
9	严兴煜, 高赐威, 陈涛, 等. 数字孪生虚拟电厂系统框架设计及其实践展望[J]. 中国电机工程学报, 2023, 43 (2): 604- 619.
	YAN Xingyu, GAO Ciwei, CHEN Tao, et al. Framework design and application prospect for digital twin virtual power plant system[J]. Proceedings of the CSEE, 2023, 43 (2): 604- 619.
10	徐峰, 何宇俊, 李建标, 等. 考虑需求响应的虚拟电厂商业机制研究综述[J]. 电力需求侧管理, 2019, 21 (3): 2- 6. DOI
	XU Feng, HE Yujun, LI Jianbiao, et al. Review of research on commercial mechanism for virtual power plant considering demand response[J]. Power Demand Side Management, 2019, 21 (3): 2- 6. DOI
11	SONG J J, LI X. Review of research on optimal scheduling method of virtual power plant[C]//2023 7th International Conference on Smart Grid and Smart Cities (ICSGSC). Lanzhou, China. IEEE, 2023: 647–652.
12	田立亭, 程林, 郭剑波, 等. 虚拟电厂对分布式能源的管理和互动机制研究综述[J]. 电网技术, 2020, 44 (6): 2097- 2108.
	TIAN Liting, CHENG Lin, GUO Jianbo, et al. A review on the study of management and interaction mechanism for distributed energy in virtual power plants[J]. Power System Technology, 2020, 44 (6): 2097- 2108.
13	李彬, 郝一浩, 祁兵, 等. 支撑虚拟电厂互动的信息通信关键技术研究展望[J]. 电网技术, 2022, 46 (5): 1761- 1770.
	LI Bin, HAO Yihao, QI Bing, et al. Key information communication technologies supporting virtual power plant interaction[J]. Power System Technology, 2022, 46 (5): 1761- 1770.
14	卫璇, 潘昭光, 王彬, 等. 云管边端架构下虚拟电厂资源集群与协同调控研究综述及展望[J]. 全球能源互联网, 2020, 3 (6): 539- 551.
	WEI Xuan, PAN Zhaoguang, WANG Bin, et al. Review on virtual power plant resource aggregation and collaborative regulation using cloud-tube-edge-end architecture[J]. Journal of Global Energy Interconnection, 2020, 3 (6): 539- 551.
15	ŠIKŠNYS L, VALSOMATZIS E, HOSE K, et al. Aggregating and disaggregating flexibility objects[J]. IEEE Transactions on Knowledge and Data Engineering, 2015, 27 (11): 2893- 2906. DOI
16	YI Z K, XU Y L, WANG X, et al. An improved two-stage deep reinforcement learning approach for regulation service disaggregation in a virtual power plant[J]. IEEE Transactions on Smart Grid, 2022, 13 (4): 2844- 2858. DOI
17	李晓舟, 秦文萍, 景祥, 等. 计及不确定风险和多主体协同的虚拟电厂参与主辅市场联合优化策略[J/OL]. 电网技术, 1–16 [2024-09-15].
	LI Xiaozhou, QIN Wenping, JING Xiang, et al. Joint optimization strategy for virtual power plant participation in primary and ancillary markets considering uncertain risks and multi-agent collaboration[J/OL]. Power System Technology, 1–16 [2024-09-15].
18	康重庆, 陈启鑫, 苏剑, 等. 新型电力系统规模化灵活资源虚拟电厂科学问题与研究框架[J]. 电力系统自动化, 2022, 46 (18): 3- 14.
	KANG Chongqing, CHEN Qixin, SU Jian, et al. Scientific problems and research framework of virtual power plant with enormous flexible distributed energy resources in new power system[J]. Automation of Electric Power Systems, 2022, 46 (18): 3- 14.
19	刘淳, 王仕俊, 赵燕玲, 等. 区块链技术在虚拟电厂交易中的应用综述[J]. 电力建设, 2023, 44 (4): 130- 144.
	LIU Chun, WANG Shijun, ZHAO Yanling, et al. Review of the application of blockchain technology in virtual power plant transactions[J]. Electric Power Construction, 2023, 44 (4): 130- 144.
20	HU Y, LIU D N, JIA H P, et al. Review of game theories applied to virtual power plants[C]//2021 International Conference on Power System Technology (POWERCON). Haikou, China. IEEE, 2021: 887–891.
21	ZHANG J, LI W. Review of revenue allocation method for virtual power plants[C]//2022 IEEE International Conference on Power Systems and Electrical Technology (PSET). Aalborg, Denmark. IEEE, 2022: 430–433.
22	郁海彬, 张煜晨, 刘扬洋, 等. 碳交易机制下多主体虚拟电厂参与电力市场的优化调度竞标策略[J]. 发电技术, 2023, 44 (5): 634- 644. DOI
	YU Haibin, ZHANG Yuchen, LIU Yangyang, et al. Optimal dispatching bidding strategy of multi-agent virtual power plant participating in electricity market under carbon trading mechanism[J]. Power Generation Technology, 2023, 44 (5): 634- 644. DOI
23	VRETTOS E, ANDERSSON G. Scheduling and provision of secondary frequency reserves by aggregations of commercial buildings[J]. IEEE Transactions on Sustainable Energy, 2015, 7 (2): 850- 864.
24	国家能源局. 国家能源局关于印发《2023年能源监管工作要点》的通知[EB/OL]. (2023.01.04) [2023.11.23]. http://zfxxgk.nea.gov.cn/2023-01/04/c_1310691552.htm.
25	山西省能源局. 关于印发《虚拟电厂建设与运营管理实施方案》的通知[EB/OL]. (2022.06.23) [2023.11.23]. http://www.shanxi.gov.cn/zfxxgk/zfxxgkzl/zc/xzgfxwj/bmgfxwj1/szfzsjg_76500/snyj_76509/202301/t20230128_7876895.shtml.
26	深圳特区报. 深圳市虚拟电厂运行指导文件发布[EB/OL]. (2023.07.17) [2023.11.23]. http://www.sz.gov.cn/cn/xxgk/zfxxgj/zwdt/content/post_10716888.html.
27	广州市工业和信息化局. 关于印发《广州市虚拟电厂实施细则》通知[EB/OL]. (2021.07.08) [2023.11.23]. https://www.gz.gov.cn/gfxwj/sbmgfxwj/gzsgyhxxhj/content/post_7364052.html.
28	仪忠凯, 许银亮, 吴文传. 考虑虚拟电厂多类电力产品的配电侧市场出清策略[J]. 电力系统自动化, 2020, 44 (22): 143- 151.
	YI Zhongkai, XU Yinliang, WU Wenchuan. Market clearing strategy for distribution system considering multiple power commodities offered by virtual power plant[J]. Automation of Electric Power Systems, 2020, 44 (22): 143- 151.
29	NGUYEN D T, LE L B. Joint optimization of electric vehicle and home energy scheduling considering user comfort preference[J]. IEEE Transactions on Smart Grid, 2013, 5 (1): 188- 199.
30	ALI SAJJAD I, CHICCO G, NAPOLI R. Definitions of demand flexibility for aggregate residential loads[J]. IEEE Transactions on Smart Grid, 2016, 7 (6): 2633- 2643.
31	ZHANG H C, HU Z C, XU Z W, et al. Evaluation of achievable vehicle-to-grid capacity using aggregate PEV model[J]. IEEE Transactions on Power Systems, 2016, 32 (1): 784- 794.
32	MÜLLER F L, SZABÓ J, SUNDSTRÖM O, et al. Aggregation and disaggregation of energetic flexibility from distributed energy resources[J]. IEEE Transactions on Smart Grid, 2017, 10 (2): 1205- 1214.
33	YI Z K, XU Y L, WANG H Z, et al. Coordinated operation strategy for a virtual power plant with multiple DER aggregators[J]. IEEE Transactions on Sustainable Energy, 2021, 12 (4): 2445- 2458. DOI
34	XU Z W, DENG T H, HU Z C, et al. Data-driven pricing strategy for demand-side resource aggregators[J]. IEEE Transactions on Smart Grid, 2016, 9 (1): 57- 66.
35	XU Z W, HU Z C, SONG Y H, et al. Risk-averse optimal bidding strategy for demand-side resource aggregators in day-ahead electricity markets under uncertainty[J]. IEEE Transactions on Smart Grid, 2015, 8 (1): 96- 105.
36	BAROT S, TAYLOR J A. A concise, approximate representation of a collection of loads described by polytopes[J]. International Journal of Electrical Power & Energy Systems, 2017, 84, 55- 63.
37	ALTHOFF M, STURSBERG O, BUSS M. Computing reachable sets of hybrid systems using a combination of zonotopes and polytopes[J]. Nonlinear Analysis: Hybrid Systems, 2010, 4 (2): 233- 249. DOI
38	QU M, DING T, WEI W, et al. An analytical method for generation unit aggregation in virtual power plants[J]. IEEE Transactions on Smart Grid, 2020, 11 (6): 5466- 5469.
39	CHEN X, DALL’ANESE E, ZHAO C H, et al. Aggregate power flexibility in unbalanced distribution systems[J]. IEEE Transactions on Smart Grid, 2019, 11 (1): 258- 269.
40	MUELLER F L, WOERNER S, LYGEROS J. Unlocking the potential of flexible energy resources to help balance the power grid[J]. IEEE Transactions on Smart Grid, 2018, 10 (5): 5212- 5222.
41	ZHAO L, ZHANG W, HAO H, et al. A geometric approach to aggregate flexibility modeling of thermostatically controlled loads[J]. IEEE Transactions on Power Systems, 2017, 32 (6): 4721- 4731. DOI
42	MADJIDIAN D, ROOZBEHANI M, DAHLEH M A. Energy storage from aggregate deferrable demand: fundamental trade-offs and scheduling policies[J]. IEEE Transactions on Power Systems, 2017, 33 (4): 3573- 3586.
43	HUGHES J T, DOMÍNGUEZ-GARCÍA A D, POOLLA K. Identification of virtual battery models for flexible loads[J]. IEEE Transactions on Power Systems, 2016, 31 (6): 4660- 4669.
44	YI Z K, XU Y L, GU W, et al. Aggregate operation model for numerous small-capacity distributed energy resources considering uncertainty[J]. IEEE Transactions on Smart Grid, 2021, 12 (5): 4208- 4224. DOI
45	孙东磊, 王宪, 孙毅, 等. 基于多面体不确定集合的电力系统灵活性量化评估方法[J]. 中国电力, 2024, 57 (9): 146- 155.
	SUN Donglei, WANG Xian, SUN Yi, et al. Polyhedral uncertainty set based power system flexibility quantitative assessment[J]. Electric Power, 2024, 57 (9): 146- 155.
46	崔屹峰, 李珍国, 贾清泉, 等. 基于参数辨识与状态估计的温控负荷响应能力动态评估[J]. 电力系统自动化, 2021, 45 (1): 150- 158.
	CUI Yifeng, LI Zhenguo, JIA Qingquan, et al. Dynamic evaluation of response potential of thermostatically controlled load based on parameter identification and state estimation[J]. Automation of Electric Power Systems, 2021, 45 (1): 150- 158.
47	CONTRERAS D A, RUDION K. Computing the feasible operating region of active distribution networks: comparison and validation of random sampling and optimal power flow based methods[J]. IET Generation, Transmission & Distribution, 2021, 15(10): 1600–1612.
48	AGEEVA L, MAJIDI M, POZO D. Analysis of feasibility region of active distribution networks[C]//2019 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). Moscow, Russia. IEEE, 2019: 1–5.
49	TAN Z F, ZHONG H W, XIA Q, et al. Estimating the robust P-Q capability of a technical virtual power plant under uncertainties[J]. IEEE Transactions on Power Systems, 2020, 35 (6): 4285- 4296. DOI
50	CHEN L, TANG Z Y, HE S J, et al. Feasible operation region estimation of virtual power plant considering heterogeneity and uncertainty of distributed energy resources[J]. Applied Energy, 2024, 362, 123000. DOI
51	CHEN X, LI N. Leveraging two-stage adaptive robust optimization for power flexibility aggregation[J]. IEEE Transactions on Smart Grid, 2021, 12 (5): 3954- 3965. DOI
52	CUI B, ZAMZAM A, BERNSTEIN A. Network-cognizant time-coupled aggregate flexibility of distribution systems under uncertainties[J]. IEEE Control Systems Letters, 2020, 5 (5): 1723- 1728.
53	WANG S Y, WU W C. Aggregate flexibility of virtual power plants with temporal coupling constraints[J]. IEEE Transactions on Smart Grid, 2021, 12 (6): 5043- 5051. DOI
54	WANG S, WU W, CHEN Q, et al. Stochastic flexibility evaluation for virtual power plant by aggregating distributed energy resources[J]. CSEE Journal of Power and Energy Systems, 2024, 10 (3): 988- 999.
55	KARIMYAN P, ABEDI M, HOSSEINIAN S H, et al. Stochastic approach to represent distributed energy resources in the form of a virtual power plant in energy and reserve markets[J]. IET Generation, Transmission & Distribution, 2016, 10 (8): 1792- 1804.
56	SONG M, AMELIN M. Purchase bidding strategy for a retailer with flexible demands in day-ahead electricity market[C]//2017 IEEE Manchester PowerTech. Manchester, UK. IEEE, 2017: 1.
57	MASHHOUR E, MOGHADDAS-TAFRESHI S M. Bidding strategy of virtual power plant for participating in energy and spinning reserve markets: part I: problem formulation[J]. IEEE Transactions on Power Systems, 2010, 26 (2): 949- 956.
58	NEZAMABADI H, SETAYESH NAZAR M. Arbitrage strategy of virtual power plants in energy, spinning reserve and reactive power markets[J]. IET Generation, Transmission & Distribution, 2016, 10 (3): 750- 763.
59	宋懿洋, 申萌均, 王剑晓, 等. 基于多参数规划的虚拟电厂边际成本函数解析表征方法[J/OL]. 电网技术: 1–11 [2024-09-16]. https://doi.org/10.13335/j.1000-3673.pst.2024.0892.
	SONG Yiyang, SHEN Mengjun, WANG Jianxiao, et al. Analytical characterization of marginal cost function for virtual power plants based on multi-parametric programming [J/OL]. Power System Technology: 1–11 [2024-09-16]. https://doi.org/10.13335/j.1000-3673.pst.2024.0892.
60	周挺, 谭玉东, 孙晋, 等. 虚拟电厂参与能量与辅助服务市场的协同优化策略[J]. 中国电力, 2024, 57 (1): 61- 70.
	ZHOU Ting, TAN Yudong, SUN Jin, et al. Collaborative optimization strategy for virtual power plant participating in energy and ancillary service market[J]. Electric Power, 2024, 57 (1): 61- 70.
61	关轶文, 张宸, 张正, 等. 计及多维源荷相关性和调峰能力的虚拟电厂规划[J/OL]. 电网技术: 1–13[2024-09-17]. https://doi.org/10.13335/j.1000-3673.pst.2024.0140.
	GUAN Yiwen, ZHANG Chen, ZHANG Zheng, et al. Virtual power plant planning considering multi-dimensional generation-load correlation and peak shaving ability [J/OL]. Power System Technology: 1–13[2024-09-17]. https://doi.org/10.13335/j.1000-3673.pst.2024.0140.
62	LI T, SHAHIDEHPOUR M. Strategic bidding of transmission-constrained GENCOs with incomplete information[J]. IEEE Transactions on Power Systems, 2005, 20 (1): 437- 447.
63	BAHRAMARA S, YAZDANI-DAMAVANDI M, CONTRERAS J, et al. Modeling the strategic behavior of a distribution company in wholesale energy and reserve markets[J]. IEEE Transactions on Smart Grid, 2017, 9 (4): 3857- 3870.
64	CUI H T, LI F X, FANG X, et al. Bilevel arbitrage potential evaluation for grid-scale energy storage considering wind power and LMP smoothing effect[J]. IEEE Transactions on Sustainable Energy, 2017, 9 (2): 707- 718.
65	KAZEMPOUR S J, CONEJO A J, RUIZ C. Strategic bidding for a large consumer[J]. IEEE Transactions on Power Systems, 2014, 30 (2): 848- 856.
66	YAZDANI-DAMAVANDI M, NEYESTANI N, CHICCO G, et al. Aggregation of distributed energy resources under the concept of multienergy players in local energy systems[J]. IEEE Transactions on Sustainable Energy, 2017, 8 (4): 1679- 1693.
67	YAZDANI-DAMAVANDI M, NEYESTANI N, SHAFIE-KHAH M, et al. Strategic behavior of multi-energy players in electricity markets as aggregators of demand side resources using a bi-level approach[J]. IEEE Transactions on Power Systems, 2017, 33 (1): 397- 411.
68	孙勇, 仪忠凯, 李宝聚, 等. 多元零售市场环境下电力聚合商有功-无功协同优化竞标策略[J]. 电力建设, 2024, 45 (10): 146- 157. DOI
	SUN Yong, YI Zhongkai, LI Baoju, et al. Active and reactive power collaborative bidding strategy for the power aggregator in multiple categories of retail markets[J]. Electric Power Construction, 2024, 45 (10): 146- 157. DOI
69	叶飞, 邵平, 王宣元, 等. 考虑购售风险的虚拟电厂双层竞标策略[J]. 电力建设, 2020, 41 (6): 28- 35.
	YE Fei, SHAO Ping, WANG Xuanyuan, et al. Bi-level bidding strategies for virtual power plants considering purchase and sale risks[J]. Electric Power Construction, 2020, 41 (6): 28- 35.
70	SONG M, AMELIN M. Price-maker bidding in day-ahead electricity market for a retailer with flexible demands[J]. IEEE Transactions on Power Systems, 2017, 33 (2): 1948- 1958.
71	DING H J, PINSON P, HU Z C, et al. Optimal offering and operating strategy for a large wind-storage system as a price maker[J]. IEEE Transactions on Power Systems, 2017, 32 (6): 4904- 4913. DOI
72	SHAFIEE S, ZAMANI-DEHKORDI P, ZAREIPOUR H, et al. Economic assessment of a price-maker energy storage facility in the Alberta electricity market[J]. Energy, 2016, 111, 537- 547. DOI
73	ARTEAGA J, ZAREIPOUR H. A price-maker/price-taker model for the operation of battery storage systems in electricity markets[J]. IEEE Transactions on Smart Grid, 2019, 10 (6): 6912- 6920.
74	KOHANSAL M, MOHSENIAN-RAD H. Price-maker economic bidding in two-settlement pool-based markets: the case of time-shiftable loads[J]. IEEE Transactions on Power Systems, 2015, 31 (1): 695- 705.
75	SHAFIEE S, ZAREIPOUR H, KNIGHT A M. Developing bidding and offering curves of a price-maker energy storage facility based on robust optimization[J]. IEEE Transactions on Smart Grid, 2017, 10 (1): 650- 660.
76	AYÓN X, GRUBER J K, HAYES B P, et al. An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands[J]. Applied Energy, 2017, 198, 1- 11. DOI
77	NGUYEN D T, LE L B. Risk-constrained profit maximization for microgrid aggregators with demand response[J]. IEEE Transactions on Smart Grid, 2014, 6 (1): 135- 146.
78	VAGROPOULOS S I, KYRIAZIDIS D K, BAKIRTZIS A G. Real-time charging management framework for electric vehicle aggregators in a market environment[J]. IEEE Transactions on Smart Grid, 2015, 7 (2): 948- 957.
79	SARKER M R, DVORKIN Y, ORTEGA-VAZQUEZ M A. Optimal participation of an electric vehicle aggregator in day-ahead energy and reserve markets[J]. IEEE Transactions on Power Systems, 2015, 31 (5): 3506- 3515.
80	VAGROPOULOS S I, BAKIRTZIS A G. Optimal bidding strategy for electric vehicle aggregators in electricity markets[J]. IEEE Transactions on Power Systems, 2013, 28 (4): 4031- 4041. DOI
81	ZHANG T, CHEN S X, GOOI H B, et al. A hierarchical EMS for aggregated BESSs in energy and performance-based regulation markets[J]. IEEE Transactions on Power Systems, 2016, 32 (3): 1751- 1760.
82	HE G N, CHEN Q X, KANG C Q, et al. Cooperation of wind power and battery storage to provide frequency regulation in power markets[J]. IEEE Transactions on Power Systems, 2016, 32 (5): 3559- 3568.
83	YI Z K, XU Y L, GU W, et al. A multi-time-scale economic scheduling strategy for virtual power plant based on deferrable loads aggregation and disaggregation[J]. IEEE Transactions on Sustainable Energy, 2019, 11 (3): 1332- 1346.
84	YI Z K, XU Y L, WEI X, et al. Robust security constrained energy and regulation service bidding strategy for a virtual power plant[J]. CSEE Journal of Power and Energy Systems, 2022, PP (99): 1- 11.
85	梁泽琪, 周云, 冯冬涵, 等. 考虑电碳绿证市场耦合的园区综合能源系统日前优化调度[J]. 电力建设, 2023, 44 (12): 43- 53. DOI
	LIANG Zeqi, ZHOU Yun, FENG Donghan, et al. Day-ahead optimal scheduling of park-integrated energy system considering electricity-carbon-green certificate market[J]. Electric Power Construction, 2023, 44 (12): 43- 53. DOI
86	刘晓军, 聂凡杰, 杨冬锋, 等. 碳捕集电厂-电转气联合运行模式下考虑绿证-碳交易机制的综合能源系统低碳经济调度[J]. 电网技术, 2023, 47 (6): 2207- 2222.
	LIU Xiaojun, NIE Fanjie, YANG Dongfeng, et al. Low carbon economic dispatch of integrated energy systems considering green certificates-carbon trading mechanism under CCPP-P2G joint operation model[J]. Power System Technology, 2023, 47 (6): 2207- 2222.
87	崔杨, 沈卓, 王铮, 等. 考虑绿证–碳排等价交互机制的区域综合能源系统绿色调度[J]. 中国电机工程学报, 2023, 43 (12): 4508- 4517.
	CUI Yang, SHEN Zhuo, WANG Zheng, et al. Green dispatch of regional integrated energy system considering green certificate-carbon emission equivalent interaction mechanism[J]. Proceedings of the CSEE, 2023, 43 (12): 4508- 4517.
88	周伟, 孙永辉, 谢东亮, 等. 计及改进阶梯型碳交易和热电联产机组灵活输出的园区综合能源系统低碳调度[J]. 电网技术, 2024, 48 (1): 61- 73.
	ZHOU Wei, SUN Yonghui, XIE Dongliang, et al. Low-carbon dispatch of park-level integrated energy system considering improved ladder-type carbon trading and flexible output of combined heat and power unit[J]. Power System Technology, 2024, 48 (1): 61- 73.
89	AN Y, ZENG B. Exploring the modeling capacity of two-stage robust optimization: variants of robust unit commitment model[J]. IEEE Transactions on Power Systems, 2014, 30 (1): 109- 122.
90	NING C, YOU F Q. Data-driven adaptive robust unit commitment under wind power uncertainty: a Bayesian nonparametric approach[J]. IEEE Transactions on Power Systems, 2019, 34 (3): 2409- 2418. DOI
91	朱誉, 仪忠凯, 陆秋瑜, 等. 基于典型场景集的虚拟电厂与配电网协同定价策略[J]. 电力建设, 2019, 40 (6): 74- 85. DOI
	ZHU Yu, YI Zhongkai, LU Qiuyu, et al. Collaborative pricing strategy of virtual power plant and distribution network considering typical scenes[J]. Electric Power Construction, 2019, 40 (6): 74- 85. DOI
92	段翩, 朱建全, 刘明波. 基于双层模糊机会约束规划的虚拟电厂优化调度[J]. 电工技术学报, 2016, 31 (9): 58- 67. DOI
	DUAN Pian, ZHU Jianquan, LIU Mingbo. Optimal dispatch of virtual power plant based on bi-level fuzzy chance constrained programming[J]. Transactions of China Electrotechnical Society, 2016, 31 (9): 58- 67. DOI
93	范松丽, 艾芊, 贺兴. 基于机会约束规划的虚拟电厂调度风险分析[J]. 中国电机工程学报, 2015, 35 (16): 4025- 4034.
	FAN Songli, AI Qian, HE Xing. Risk analysis on dispatch of virtual power plant based on chance constrained programming[J]. Proceedings of the CSEE, 2015, 35 (16): 4025- 4034.
94	鲍谚, 石锦凯, 陈世豪. 考虑负荷预测不确定性的快充站储能鲁棒实时控制策略[J]. 电力系统自动化, 2023, 47 (10): 107- 116. DOI
	BAO Yan, SHI Jinkai, CHEN Shihao. Robust real-time control strategy for energy storage in fast charging station considering load forecasting uncertainty[J]. Automation of Electric Power Systems, 2023, 47 (10): 107- 116. DOI
95	ZHAO H T, WANG X Y, WANG B, et al. A multi time-scale robust aggregation model for virtual power plant based on rolling correction[C]//2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2). Chengdu, China. IEEE, 2022: 2574–2579.
96	闫鹏, 曾四鸣, 李铁成, 等. 基于改进量子遗传算法的虚拟电厂在多时间尺度下参与AGC优化调度[J]. 电网与清洁能源, 2023, 39 (3): 23- 32. DOI
	YAN Peng, ZENG Siming, LI Tiecheng, et al. Optimal scheduling of virtual power plant participating in AGC based on improved quantum genetic algorithm on multi-time scale[J]. Power System and Clean Energy, 2023, 39 (3): 23- 32. DOI
97	KHAVARI F, BADRI A, ZANGENEH A. Energy management in multi-microgrids via an aggregator to override point of common coupling congestion[J]. IET Generation, Transmission & Distribution, 2019, 13(5): 634–642.
98	ASIMAKOPOULOU G E, DIMEAS A L, HATZIARGYRIOU N D. Leader-follower strategies for energy management of multi-microgrids[J]. IEEE Transactions on Smart Grid, 2013, 4 (4): 1909- 1916.
99	DU Y, LI F X. A hierarchical real-time balancing market considering multi-microgrids with distributed sustainable resources[J]. IEEE Transactions on Sustainable Energy, 2018, 11 (1): 72- 83.
100	周步祥, 张越, 臧天磊, 等. 基于区块链的多虚拟电厂主从博弈优化运行[J]. 电力系统自动化, 2022, 46 (1): 155- 163.
	ZHOU Buxiang, ZHANG Yue, ZANG Tianlei, et al. Blockchain-based stackelberg game optimal operation of multiple virtual power plants[J]. Automation of Electric Power Systems, 2022, 46 (1): 155- 163.

[1]	WANG Jinfeng, LI Jinpeng, XU Yinliang, LIU Haitao, HE Jinxiong, XU Jianyuan. Distributed Optimization for VPP and Distribution Network Operation Considering Uncertainty and Green Certificate Market [J]. Electric Power, 2025, 58(4): 21-30, 192.
[2]	ZHAO Tong, LI Xuesong, ZHOU Hao, DING Yu, YANG Bin, WANG Wentao, WANG Peng. Electricity Carbon Coupled Market Modeling Method and Market Optimization Mechanism Based on Dynamic Carbon Emission Intensity [J]. Electric Power, 2025, 58(4): 31-43.
[3]	Jie WANG, Fei ZHENG, Pengcheng ZHANG, Ludong CHEN, Hua GAO, Jingrong MENG. Model of High-Proportion New Energy Distribution Network Planning Based on Data-Driven Approach [J]. Electric Power, 2025, 58(3): 175-182.
[4]	Yening LAI, Zhongqing SUN, Zhiping LU, Qin LIU. Power Grid Optimization Operation and Resilience Improvement Strategy Considering the Participation of Energy Storage Resource Aggregation [J]. Electric Power, 2025, 58(2): 57-65.
[5]	Mingbing LI, Qiang LI, Xiyang GUAN, Haoyang ZHOU, Rui LU, Yankun FENG. Market Oriented Low-Carbon Optimal Scheduling of Virtual Power Plants Considering Multiple User-Side Resources Coordination [J]. Electric Power, 2025, 58(2): 66-76.
[6]	Donglei SUN, Yi SUN, Rui LIU, Pengkai SUN, Yumin ZHANG. Maximum Accommodation Capacity Decomposition of Distributed Renewable Power Generation Considering Multi-Level Distribution Network [J]. Electric Power, 2024, 57(8): 108-116.
[7]	Ke YANG, Dong WANG, Da LI, Wangjun ZHANG, Ga XIANG, Jun LI. Network Security Risk Assessment Index System and Calculation for Virtual Power Plant [J]. Electric Power, 2024, 57(8): 130-137.
[8]	Zhengnan GAO, Nan JIANG, Qixin CHEN, Jiang XU, Haili WANG, Li XIN, Qinggui XU. Construction Experience of German Electricity Market Adapting to Energy Transition [J]. Electric Power, 2024, 57(6): 204-214.
[9]	Wenlong LI, Yun ZHOU, Ling LUO, Tiantian CHEN, Donghan FENG. Carbon Allocation Throughout the Entire Process of Electric Energy Trading Considering Spot Trading [J]. Electric Power, 2024, 57(5): 99-112.
[10]	Hu TAN, Xiaoliang WANG, Tingting XU, Ke ZHAO, Lianchao SU, Wenyu ZHANG, Zheng XIN. Economic and Technological Optimization of Hybrid Rural Microgrid with Wind, PV, Biogas, Storage, AC, and DC [J]. Electric Power, 2024, 57(3): 27-33.
[11]	Juanjuan GUO, Di SHEN, Pu TONG, Kun YAN, Xiaofan ZHANG, Fang HE. Economic Evaluation Method and Parameter Optimization for Third-Generation Nuclear Power in China [J]. Electric Power, 2024, 57(3): 206-212, 223.
[12]	Zhiyuan GAO, Weijin ZHUANG, Jian GENG, Feng LI, Bike XUE, Xiaolei YANG, Keju BAI. The Regulation Mechanism of Electricity Market on Load Side Resources Based on the Economic Person Hypothesis [J]. Electric Power, 2024, 57(3): 213-223.
[13]	Chaoying LI, Qinliang TAN. Market Trading Strategy for Thermal Power Enterprise in New Power System Based on Agent Modeling [J]. Electric Power, 2024, 57(2): 212-225.
[14]	Xingping ZHANG, Teng WANG, Xinyue ZHANG, Haonan ZHANG. Bidding Strategy for Thermal Power Generation Companies Based on Multi-agent Deep Deterministic Policy Gradient Algorithm [J]. Electric Power, 2024, 57(11): 161-172.
[15]	Tianqi SONG, Zhipeng LV, Zhenhao SONG, Yunting MA, Zhihui ZHANG, Shan ZHOU, Hao LI. Research and Thinking on the Aggregation and Dispatching Control Framework of Virtual Power Plant's Large Scale Flexible Resources [J]. Electric Power, 2024, 57(1): 2-8.