Review of optimal dispatching technology and market mechanism design for virtual power plants

doi:10.3969/j.issn.2097-0706.2022.02.009

Abstract

Abstract:

In order to cope with the continuous aggravation of environmental pollution and increasing shortage of fossil fuels,the proportion of renewable energy such as wind power and photovoltaic in power grid has been soaring.However,renewable energy power generation is intermittent and fluctuating,and its access points are scattered,which increases the difficulty of safe and stable operation of the system.Virtual power plants provide a new train of thought for the problem above.The concept and implementation architecture of a VPP are expounded.The key technologies for VPPs to participate in power system optimal operation scheduling are analyzed from three perspectives,integrated energy,electric vehicles and renewable energy.The technologies realize the interaction between electricity,heat,gas and other integrated energy, lower the operating cost of the system,alleviate the side effects of disordered charging and discharging of electric vehicles on the power grid,and suppressed the intermittent and fluctuating output of renewable energy as well.In addition,the VPP's market strategies based on game theory and other methods under market environment are analyzed.Sorting out the typical engineering applications of VPPs can provide reference for the construction and development of VPPs in China.

Key words: virtual power plant, integrated energy, electric vehicle, renewable energy, carbon neutrality, market mechanism, demand response, distributed energy storage, energy internet

CLC Number:

TK01：TM73

ZHANG Kaijie, DING Guofeng, WEN Ming, HUI Hongxun, DING Yi, HE Min, CHU Jiefeng, XIE Kang, YU Chutian, ZHANG Lijun. Review of optimal dispatching technology and market mechanism design for virtual power plants[J]. Integrated Intelligent Energy, 2022, 44(2): 60-72.

Figures/Tables 4

References 87

[1]	KARDAKOS E G, SIMOGLOU C K, BAKIRTZIS A G. Optimal offering strategy of a virtual power plant:A stochastic bi-level approach[J]. IEEE Transaction on Smart Grid, 2016,7(2):794-806.
[2]	FARHANGI H. The path of the smart grid[J]. IEEE Power and Energy Magazine, 2010,8(1):18-28.
[3]	ZIADI Z, TAIRA S, OSHIRO M, et al. Optimal power scheduling for smart grids considering controllable loads and high penetration of photovoltaic generation[J]. IEEE Transactions on Smart Grid, 2014,5(5):2350-2359. doi: 10.1109/TSG.2014.2323969
[4]	HUI H X, DING Y, SHI Q X, et al. 5G network-based internet of things for demand response in smart grid:A survey on application potential[J]. Applied Energy, 2020,257:113972-113986. doi: 10.1016/j.apenergy.2019.113972
[5]	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):1-13. doi: 10.1186/s41601-019-0115-7
[6]	HILL C A, SUCH M C, CHEN D, et al. Battery energy storage for enabling integration of distributed solar power generation[J]. IEEE Transaction on Smart Grid, 2012,3(2):850-857. doi: 10.1109/TSG.2012.2190113
[7]	LEE D, KIM J, BALDICK R. Stochastic optimal control of the storage system to limit ramp rates of wind power output[J]. IEEE Transaction on Smart Grid, 2013,4(4):2256-2265. doi: 10.1109/TSG.2013.2285524
[8]	孔见虹, 李平, 黄未, 等. 基于分布式储能的光伏并网系统调频策略研究[J]. 电力电子技术, 2020,54(4):80-83,96.
	KONG Jianhong, LI Ping, HUANG Wei, et al. Research on frequency modulation strategy of photovoltaic grid-connected system based on distributed energy storage[J]. Power Electronics, 2020,54(4):80-83,96.
[9]	王海冰, 王简, 王承民, 等. 计及风险约束的虚拟电厂能量管理建模[J]. 中国电机工程学报, 2017,37(20):5942-5950.
	WANG Haibing, WANG Jian, WANG Chengmin, et al. Risk-constrained energy management modeling of virtual power plant[J]. Proceedings of the CSEE, 2017,37(20):5942-5950.
[10]	刘吉臻, 李明扬, 房方, 等. 虚拟发电厂研究综述[J]. 中国电机工程学报, 2014,34(29):5103-5111.
	LIU Jizhen, LI Mingyang, FANG Fang, et al. Review on virtual power plants[J]. Proceedings of the CSEE, 2014,34(29):5103-5111.
[11]	刘思源, 艾芊, 郑建平, 等. 多时间尺度的多虚拟电厂双层协调机制与运行策略[J]. 中国电机工程学报, 2018,38(3):753-761.
	LIU Siyuan, AI Qian, ZHENG Jianping, et al. Bi-level coordination mechanism and operation strategy of multi-time scale multiple virtual power plants[J]. Proceedings of the CSEE, 2018,38(3):753-761.
[12]	别朝红, 胡国伟, 谢海鹏, 等. 考虑需求响应的含风电电力系统的优化调度[J]. 电力系统自动化, 2014,38(13):115-120.
	BIE Chaohong, HU Weiguo, XIE Haipeng, et al. Optimal dispatch for wind power integrated systems considering demand response[J]. Automation of Electric Power Systems, 2014,38(13):115-120.
[13]	YU R, JAN K, SONIA M. Storage size determination for grid-connected photovoltaic systems[J]. IEEE Transactions on Sustainable Energy, 2013,4(1):68-81. doi: 10.1109/TSTE.2012.2199339
[14]	晋宏杨, 孙宏斌, 郭庆来, 等. 含大规模储热的光热电站-风电联合系统多日自调度方法[J]. 电力系统自动化, 2016,40(11):17-23.
	JIN Hongyang, SUN Hongbin, GUO Qinglai, et al. Multi-day self-scheduling method for combined system of CSP plants and wind power with large-scale thermal energy storage contained[J]. Automation of Electric Power Systems, 2016,40(11):17-23.
[15]	HOUWING M, PAPAEFTHYMIOU G, HEIJNEN P W, et al. Balancing wind power with virtual power plants of micro-CHPs[C]//2009 IEEE Bucharest PowerTech,Bucharest,Romania, 2009.
[16]	马腾飞, 吴俊勇, 郝亮亮, 等. 基于能源集线器的微能源网能量流建模及优化运行分析[J]. 电网技术, 2018,42(1):179-186.
	MA Tengfei, WU Junyong, HAO Liangliang, et al. Energy flow modeling and optimal operation analysis of micro energy grid based on energy hub[J]. Power System Technology, 2018,42(1):179-186.
[17]	胡泽春, 宋永华, 徐智威, 等. 电动汽车接入电网的影响与作用[J]. 中国电机工程学报, 2012,32(4):1-10.
	HU Zechun, SONG Yonghua, XU Zhiwei, et al. Impacts and utilization of electric vehicles integration into power system[J]. Proceedings of the CSEE, 2012,32(4):1-10.
[18]	高赐威, 张亮. 电动汽车充电对电网影响综述[J]. 电网技术, 2011,32(5):127-131.
	GAO Ciwei, ZHANG Liang. A survey of influence of electrics vehicle charging on power grid[J]. Power System Technology, 2011,32(5):127-131.
[19]	孙国强, 袁智, 耿天翔, 等. 含电动汽车的虚拟电厂鲁棒随机优化调度[J]. 电力系统自动化, 2017,41(6):44-50,79.
	SUN Guoqiang, YUAN Zhi, GENG Tianxiang, et al. Robust stochastic optimal dispatching of virtual power plant containing plug-in electric vehicles[J]. Automation of Electric Power Systems, 2017,41(6):44-50,79.
[20]	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 Trans on Power Systems, 2011,26(2):949-956. doi: 10.1109/TPWRS.2010.2070884
[21]	梅生伟, 刘锋, 魏韡. 工程博弈论基础及电力系统应用[M]. 北京: 科学出版社, 2016:65-67.
[22]	卫志农, 余爽, 孙国强, 等. 虚拟电厂的概念与发展[J]. 电力系统自动化, 2013,37(13):1-9.
	WEI Zhinong, YU Shuang, SUN Guoqiang, et al. Concept and development of virtual power plant[J]. Automation of Electric Power Systems, 2013,37(13):1-9.
[23]	姜海洋, 谭忠富, 胡庆辉, 等. 用户侧虚拟电厂对发电产业节能减排影响分析[J]. 中国电力, 2010,43(6):37-40.
	JIANG Haiyang, TAN Zhongfu, HU Qinghui, et al. Action analysis of nominal power plants on energy saving and emission controlling of power industry[J]. Electric Power, 2010,43(6):37-40.
[24]	张高, 王旭, 蒋传文, 等. 采用双层优化调度的虚拟电厂经济性分析[J]. 电网技术, 2016,40(8):2295-2301.
	ZHANG Gao, WANG Xu, JIANG Chuanwen, et al. Economic analysis of virtual power plants based on bi-level optimization dispatch[J]. Power System Technology, 2016,40(8):2295-2301.
[25]	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.
	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.
[26]	夏榆杭, 刘俊勇. 基于分布式发电的虚拟发电厂研究综述[J]. 电力自动化设备, 2016,36(4):100-106,115.
	XIA Yuhang, LIU Junyong. Review of virtual power plant based on distributed generation[J]. Electric Power Automation Equipment, 2016,36(4):100-106,115.
[27]	吴威辰, 王旭, 蒋传文, 等. 计及需求侧响应的虚拟电厂运行优化研究[J]. 新能源发电控制技术, 2019,41(2):29-32,94.
	WU Weichen, WANG Xu, JIANG Chuanwen, et al. Research on operation optimization of virtual power plants under consideration of demand-side response[J]. The New Energy Power Control Technology, 2019,41(2):29-32,94.
[28]	张涛, 王成, 王凌云, 等. 考虑虚拟电厂参与的售电公司双层优化调度模型[J]. 电网技术, 2019,43(3):952-960.
	ZHANG Tao, WANG Cheng, WANG Lingyun, et al. A bi-level optimal dispatching model of electricity retailers integrated with VPPs[J]. Power System Technology, 2019,43(3):952-960.
[29]	刘祚宇. 含电动汽车虚拟电厂的规划与优化调度[D]. 杭州:浙江大学, 2019.
[30]	周亦洲, 孙国强, 黄文进, 等. 计及电动汽车和需求响应的多类电力市场下虚拟电厂竞标模型[J]. 电网技术, 2017,41(6):1759-1766.
	ZHOU Yizhou, SUN Guoqiang, HUANG Wenjin, et al. Strategic bidding model for virtual power plant in different electricity markets considering electric vehicles and demand response[J]. Power System Technology, 2017,41(6):1759-1766.
[31]	赵洪山, 刘然. 奖惩机制下虚拟电厂优化调度效益分析[J]. 电网技术, 2017,41(9):2840-2846.
	ZHAO Hongshan, LIU Ran. Benefit analysis of optimal schedule of virtual power plant under reward-punishment mechanism[J]. Power System Technology, 2017,41(9):2840-2846.
[32]	孙国强, 周亦洲, 卫志农, 等. 能量和旋转备用市场下虚拟电厂热电联合调度鲁棒优化模型[J]. 中国电机工程学报, 2017,37(11):3118-3128.
	SUN Guoqiang, ZHOU Yizhou, WEI Zhinong, et al. Thermal and electrical scheduling of a virtual power plant for participating in energy and spinning reserve markets based on robust optimization[J]. Proceedings of the CSEE, 2017,37(11):3118-3128.
[33]	袁桂丽, 王琳博, 王宝源. 基于虚拟电厂“热电解耦”的负荷优化调度及经济效益分析[J]. 中国电机工程学报, 2017,37(17):4974-4985.
	YUAN Guili, WANG Linbo, WANG Baoyuan. Optimal dispatch of heat-power load and economy benefit analysis based on decoupling of heat and power of virtual power plant[J]. Proceedings of the CSEE, 2017,37(17):4974-4985.
[34]	袁桂丽, 贾新潮, 房方, 等. 虚拟电厂源荷双侧热电联合随机优化调度[J]. 电网技术, 2020,44(8):2932-2940.
	YUAN Guili, JIA Xinchao, FANG Fang, et al. Joint stochastic optimal scheduling of heat and power considering source-side and load-side of virtual power plant[J]. Power System Technology, 2020,44(8):2932-2940.
[35]	周亦洲, 孙国强, 黄文进, 等. 多区域虚拟电厂综合能源协调调度优化模型[J]. 中国电机工程学报, 2017,37(23):6780-6790.
	ZHOU Yizhou, SUN Guoqiang, HUANG Wenjin, et al. Optimized multi-regional integrated energy coordinated scheduling of a virtual power plant[J]. Proceedings of the CSEE, 2017,37(23):6780-6790.
[36]	许福鹿, 周任军, 曹俊波, 等. 多种市场下虚拟电厂电-热-气协调优化调度[J]. 电力系统及其自动化学报, 2019,31(9):35-42.
	XU Fulu, ZHOU Renjun, CAO Junbo, et al. Coordinated optimal dispatching of power-heat-gas for virtual power plant participating in multiple markets[J]. Proceedings of the CSU-EPSA, 2019,31(9):35-42.
[37]	张亚朋, 穆云飞, 贾宏杰, 等. 电动汽车虚拟电厂的多时间尺度响应能力评估模型[J]. 电力系统自动化, 2019,43(12):94-103.
	ZHANG Yapeng, MU Yunfei, JIA Hongjie, et al. Response capability evaluation model with multiple time scales for electric vehicle virtual power plant[J]. Automation of Electric Power Systems, 2019,43(12):94-103.
[38]	卢志刚, 王荟敬, 赵号, 等. 含V2G的虚拟电厂双层逆鲁棒优化调度策略[J]. 电网技术, 2017,41(4):1245-1252.
	LU Zhigang, WANG Huijing, ZHAO Hao, et al. Strategy of bi-level inverse robust optimization dispatch of virtual power plant containing V2G[J]. Power System Technology, 2017,41(4):1245-1252.
[39]	刘永前, 林爱美, 阎洁, 等. 基于深度学习的风光场群功率预测方法研究[J]. 分布式能源, 2021,6(2):14-21.
	LIU Yongqian, LIN Aimei, YAN Jie, et al. Research on power forecasting method for wind farms and photovoltaic stations based on deep learning[J]. Distributed Energy, 2021,6(2):14-21.
[40]	崔杨, 陈正洪, 许沛华. 基于机器学习的集群式风光一体短期功率预测技术[J]. 中国电力, 2020,53(3):1-7.
	CUI Yang, CHEN Zhenghong, XU Peihua. Short-term power prediction for wind farm and solar plant clusters based on machine learning method[J]. Electric Power, 2020,53(3):1-7.
[41]	王函. 风光发电功率与用电负荷联合预测方法研究[D]. 北京:华北电力大学, 2021.
[42]	刘小瑞. 基于数据驱动的风电场功率预测及其在源荷协调中的应用[D]. 湘潭:湘潭大学, 2018.
[43]	韩晓娟, 程成, 籍天明, 等. 计及电池使用寿命的混合储能系统容量优化模型[J]. 中国电机工程学报, 2013,33(34):91-97.
	HAN Xiaojuan, CHENG Cheng, JI Tianming, et al. Capacity optimal modeling of hybrid energy storage systems considering battery life[J]. Proceedings of the CSEE, 2013,33(34):91-97.
[44]	齐军, 杨帅帅, 张红光, 等. 基于机会约束规划的含储能虚拟电厂调度模型[J]. 工业技术创新, 2019,6(1):70-76.
	QI Jun, YANG Shuaishuai, ZHANG Hongguang, et al. Dispatch model for energy storage virtual power plant based on chance constrained programming[J]. Industrial Technology Innovation, 2019,6(1):70-76.
[45]	严干贵, 冯晓东, 李军徽. 用于松弛调峰瓶颈的储能系统容量配置方法[J]. 中国电机工程学报, 2012,32(28):27-35.
	YAN Gangui, FENG Xiaodong, LI Junhui. Optimization of energy storage system capacity for relaxing peak load regulation bottlenecks[J]. Proceedings of the CSEE, 2012,32(28):27-35.
[46]	韦立坤, 赵波, 吴红斌, 等. 虚拟电厂下计及大规模分布式光伏的储能系统配置优化模型[J]. 电力系统自动化, 2015,39(23):66-74.
	WEI Likun, ZHAO Bo, WU Hongbin, et al. Optimal allocation model of energy storage system in virtual power plant environment with a high penetration of distributed photovoltaic generation[J]. Automation of Electric Power Systems, 2015,39(23):66-74.
[47]	牛东晓, 赵东来, 杨尚东, 等. 考虑不确定性和储能系统的虚拟电厂与能效电厂联合调度优化模型及仿真应用[J]. 中南大学学报(自然科学版), 2019,50(7):1736-1743.
	NIU Dongxiao, ZHAO Donglai, YANG Shangdong, et al. Cooperative scheduling optimization model and simulation application for virtual power plant and efficiency power plant considering uncertainty and energy storage system[J]. Journal of Central South University (Science and Technology), 2019,50(7):1736-1743.
[48]	卫志农, 陈妤, 黄文进, 等. 考虑条件风险价值的虚拟电厂多电源容量优化配置模型[J]. 电力系统自动化, 2018,42(4):39-46.
	WEI Zhinong, CHEN Yu, HUANG Wenjin, et al. Optimal allocation model for multi-energy capacity of virtual power plant considering conditional value-at-risk[J]. Automation of Electric Power Systems, 2018,42(4):39-46.
[49]	吕梦璇, 娄素华, 刘建琴, 等. 含高比例风电的虚拟电厂多类型备用协调优化[J]. 中国电机工程学报, 2018,38(10):2874-2882.
	LÜ Mengxuan, LOU Suhua, LIU Jianqin, et al. Coordinated optimization of multi-type reserve in virtual power plant accommodated high shares of wind power[J]. Proceedings of the CSEE, 2018,38(10):2874-2882.
[50]	陈厚合, 王子璇, 张儒峰, 等. 含虚拟电厂的风电并网系统分布式优化调度建模[J]. 中国电机工程学报, 2019,39(9):2615-2624.
	CHEN Houhe, WANG Zixuan, ZHANG Rufeng, et al. Decentralized optimal dispatching modeling for wind power integrated power system with virtual power plant[J]. Proceedings of the CSEE, 2019,39(9):2615-2624.
[51]	徐辉, 焦扬, 蒲雷, 等. 计及不确定性和需求响应的风光燃储集成虚拟电厂随机调度优化模型[J]. 电网技术, 2017,41(11):3590-3597.
	XU Hui, JIAO Yang, PU Lei, et al. Stochastic scheduling optimization model for virtual power plant of integrated wind-photovoltaic-energy storage system considering uncertainty and demand response[J]. Power System Technology, 2017,41(11):3590-3597.
[52]	彭院院, 周任军, 李斌, 等. 计及光热发电特性的光-风-火虚拟电厂双阶段优化调度[J]. 电力系统及其自动化学报, 2020,32(4):21-28.
	PENG Yuanyuan, ZHOU Renjun, LI Bin, et al. Two-stage optimal dispatch model for solar-wind-thermal virtual power plant considering the characteristic of concentrating solar power[J]. Proceedings of the CSU-EPSA, 2020,32(4):21-28.
[53]	周任军, 徐健, 王仰之, 等. 利用市场交易奖惩措施的风电-垃圾焚烧虚拟电厂优化运行[J]. 电力系统及其自动化学报, 2020,32(10):90-96.
	ZHOU Renjun, XU Jian, WANG Yangzhi, et al. Optimized operation of virtual power plant with wind power and waste incineration based on market trading incentives[J]. Proceedings of the CSU-EPSA, 2020,32(10):90-96.
[54]	吕蒙. 考虑风光不确定性的微网多时间尺度优化调度[D]. 西安:西安理工大学, 2021.
[55]	李旭东, 艾欣, 胡俊杰, 等. 计及碳交易机制的核-火-虚拟电厂三阶段联合调峰策略研究[J]. 电网技术, 2019,43(7):2460-2470.
	LI Xudong, AI Xin, HU Junjie, et al. Three-stage combined peak regulation strategy for nuclear-thermal-virtual power plant considering carbon trading mechanism[J]. Power System Technology, 2019,43(7):2460-2470.
[56]	魏向欣, 何涛, 李一航, 等. 5G网络切片承载电力系统业务的时延特性研究[J]. 电力信息与通信技术, 2019,17(8):7-12.
	WEI Xiangxin, HE Tao, LI Yihang, et al. Research on time delay characteristics of 5G network slice in carrying power communication service[J]. Electric Power ICT, 2019,17(8):7-12.
[57]	张放, 程林, 黎雄, 等. 广域闭环控制系统时延的测量及建模(一):通信时延及操作时延[J]. 中国电机工程学报, 2015,35(22):5768-5777.
	ZHANG Fang, CHENG Lin, LI Xiong, et al. Delay measurement and modeling in a wide-area closed-loop control system,Part I:Communication delay and operational delay[J]. Proceedings of the CSEE, 2015,35(22):5768-5777.
[58]	张放, 程林, 黎雄, 等. 广域闭环控制系统时延的测量及建模(二):闭环时延[J]. 中国电机工程学报, 2015,35(23):5995-6002.
	ZHANG Fang, CHENG Lin, LI Xiong, et al. Delay measurement and modeling in a wide-area closed-loop control system,Part II:Closed-loop delay[J]. Proceedings of the CSEE, 2015,35(23):5995-6002.
[59]	张放, 程林, 黎雄, 等. 广域闭环控制系统时延的分层预测补偿[J]. 中国电机工程学报, 2014,34(19):3194-3201.
	ZHANG Fang, CHENG Lin, LI Xiong, et al. Prediction based on hierarchical compensation for delays of wide-area closed-loop control systems[J]. Proceedings of the CSEE, 2014,34(19):3194-3201.
[60]	惠红勋. 温控负荷参与电力系统动态响应的建模与控制方法研究[D]. 杭州:浙江大学, 2020.
[61]	刘扬洋, 蒋传文, 谭胜敏, 等. 考虑风险调整资本收益率阈值约束的虚拟电厂优化调度策略[J]. 中国电机工程学报, 2016,36(17):4617-4626.
	LIU Yangyang, JIANG Chuanwen, TAN Shengmin, et al. Optimal dispatch of virtual power plant considering risk adjusted return on capital constraints[J]. Proceedings of the CSEE, 2016,36(17):4617-4626.
[62]	王宣元, 刘敦楠, 刘蓁, 等. 泛在电力物联网下虚拟电厂运营机制及关键技术[J]. 电网技术, 2019,43(9):3175-3183.
	WANG Xuanyuan, LIU Dunnan, LIU Zhen, et al. Operation mechanism and key technologies of virtual power plant under ubiquitous internet of things[J]. Power System Technology, 2019,43(9):3175-3183.
[63]	杨甲甲, 赵俊华, 文福拴, 等. 含电动汽车和风电机组的虚拟发电厂竞价策略[J]. 电力系统自动化, 2014,38(13):92-102.
	YANG Jiajia, ZHAO Junhua, WEN Fushuan, et al. Development of bidding strategies for virtual power plants considering uncertain outputs from plug-in electric vehicles and wind generators[J]. Automation of Electric Power Systems, 2014,38(13):92-102.
[64]	邵炜晖, 许维胜, 徐志宇, 等. 基于虚拟电厂技术的未来智能电网用户并网规则设计及仿真[J]. 电力系统自动化, 2015,39(17):140-146.
	SHAO Weihui, XU Weisheng, XU Zhiyu, et al. Design and simulation of grid connection mechanism for future smart grid users based on virtual power plant technology[J]. Automation of Electric Power Systems, 2015,39(17):140-146.
[65]	何奇琳, 艾芊. 售电侧放开环境下含需求响应虚拟电厂的电力市场竞价策略[J]. 电力建设, 2019,40(2):1-10.
	HE Qilin, AI Qian. Bidding strategy of electricity market including virtual power plant considering demand response under retail power market deregulation[J]. Electric Power Construction, 2019,40(2):1-10.
[66]	方燕琼, 甘霖, 艾芊, 等. 基于主从博弈的虚拟电厂双层竞标策略[J]. 电力系统自动化, 2017,41(14):61-69.
	FANG Yanqiong, GAN Lin, AI Qian, et al. Stackelberg game based bi-level bidding strategy for virtual power plant[J]. Automation of Electric Power Systems, 2017,41(14):61-69.
[67]	张高, 王旭, 蒋传文. 基于主从博弈的含电动汽车虚拟电厂协调调度[J]. 电力系统自动化, 2018,42(11):48-55.
	ZHANG Gao, WANG Xu, JIANG Chuanwen. Stackelberg game based coordinated dispatch of virtual power plant considering electric vehicle management[J]. Automation of Electric Power Systems, 2018,42(11):48-55.
[68]	董雷, 涂淑琴, 李烨, 等. 基于元模型优化算法的主从博弈多虚拟电厂动态定价和能量管理[J]. 电网技术, 2020,44(3):973-983.
	DONG Lei, TU Shuqin, LI Ye, et al. A stackelberg game model for dynamic pricing and energy management of multiple virtual power plants using metamodel-based optimization method[J]. Power System Technology, 2020,44(3):973-983.
[69]	路尧, 刘继春, 许立雄. 非合作博弈下考虑用户满意度的虚拟电厂经济优化运行[J]. 分布式能源, 2017,2(1):23-29.
	LU Yao, LIU Jichun, XU Lixiong. Economic optimization operation of virtual power plant considering the users' satisfaction based on non-cooperative game theory[J]. Distributed Energy, 2017,2(1):23-29.
[70]	孙国强, 钱苇航, 黄文进, 等. 考虑配电网安全性的虚拟电厂优化调度博弈模型[J]. 电力自动化设备, 2019,39(5):7-14.
	SUN Guoqiang, QIAN Weihang, HUANG Wenjin, et al. Optimal dispatch game model for virtual power plant considering security of distribution network[J]. Electric Power Automation Equipment, 2019,39(5):7-14.
[71]	王晛, 张华君, 张少华. 风电和电动汽车组成虚拟电厂参与电力市场的博弈模型[J]. 电力系统自动化, 2019,43(3):155-162.
	WANG Xian, ZHANG Huajun, ZHANG Shaohua. Game model of electricity market involving virtual power plant composed of wind power and electric vehicles[J]. Automation of Electric Power Systems, 2019,43(3):155-162.
[72]	SOTER S, BERTLING F. Adjustable converter for injection of fuel cell power as a part of a virtual power plant[C]//IEEE 35th Annual Power Electronic Specialists Conference,Aachen,Germany, 2004.
[73]	卫志农, 余爽, 孙国强, 等. 虚拟电厂欧洲研究项目述评[J]. 电力系统自动化, 2013,37(21):196-202.
	WEI Zhinong, YU Shuang, SUN Guoqiang, et al. Review on European research project of virtual power plant[J]. Automation of Electric Power Systems, 2013,37(21):196-202.
[74]	KOK K J, WARMER J C, KAMPHUIS G I. The power matcher:Multi-agent control of electricity demand and supply[J]. IEEE Intelligent System, 2006,21(2):89-90.
[75]	BINDING C, GANTENBEIN D, JANSEN B, et al. Electric vehicle fleet integration in the Danish Edison project—A virtual power plant on the island of Bornholm[C]//IEEE PES General Meeting,Minneapolis,MN,USA, 2010.
[76]	FENN B, HOPP O, AHNER M. Advanced technologies of demand side integration by VPPs and through smart metering in households-experiences from a lighthouse project[C]//CIGRE 2012,Paris,France, 2012.
[77]	阮文俊, 刘莎, 李扬. 美国需求响应综述[J]. 电力需求侧管理, 2013,15(2):61-64.
	RUAN Wenjun, LIU Sha, LI Yang. Overview of demand response in the USA[J]. Power Demand Side Management, 2013,15(2):61-64.
[78]	应志玮, 余涛, 黄宇鹏, 等. 上海虚拟电厂运营市场出清的研究与实现[J]. 电力学报, 2020,35(2):129-134.
	YING Zhiwei, YU Tao, HUANG Yupeng, et al. Research on clearing the operation market of Shanghai virtual power plant[J]. Journal of Electric Power, 2020,35(2):129-134.
[79]	谢康, 张凯杰, 栾开宁, 等. 电力体制改革背景下的需求响应积分方案探索[J]. 电力需求侧管理, 2019,21(3):7-10.
	XIE Kang, ZHANG Kaijie, LUAN Kaining, et al. Exploration of demand response score scheme under the background of electric power system reform[J]. Power Demand Side Management, 2019,21(3):7-10.
[80]	张勉荣. 中国南方电网公司的电力需求侧管理实践[J]. 电力需求侧管理, 2011,13(1):7-8.
	ZHANG Mianrong. DSM practice of China Southern Power Grid[J]. Power Demand Side Management, 2011,13(1):7-8.
[81]	邓宇鑫, 王磊, 李扬, 等. 温控负荷直接负荷控制策略与优化调度[J]. 电力系统及其自动化学报, 2015,27(6):18-25.
	DENG Yuxin, WANG Lei, LI Yang, et al. Direct load control strategies and optimization scheduling of thermostatically controlled loads[J]. Proceedings of the CSU-EPSA, 2015,27(6):18-25.
[82]	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):99-108.
	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):99-108.
[83]	刘林鹏, 陈嘉俊, 朱建全, 等. 风储联合参与电能量与快速调频市场的优化投标策略[J]. 华电技术, 2021,43(9):46-53.
	LIU Linpeng, CHEN Jiajun, ZHU Jianquan, et al. Optimization bidding strategy for wind power and energy storage participating in energy market[J]. Huadian Technology, 2021,43(9):46-53.
[84]	姚垚, 张沛超, 王永权. 温控负荷参与快速频率调整的双层控制方法[J]. 中国电机工程学报, 2018,38(17):4987-4998,5296.
	YAO Yao, ZHANG Peichao, WANG Yongquan. A two-layer control method for thermostatically controlled loads to provide fast frequency regulation[J]. Proceedings of the CSEE, 2018,38(17):4987-4998,5296.
[85]	张青. 温控负荷聚合建模及其功率控制[D]. 南京:东南大学, 2016.
[86]	王兴兴, 孙建桥, 陈明. 储能火电联合调频系统设计与研究[J]. 华电技术, 2020,42(4):72-76.
	WANG Xingxing, SUN Jianqiao, CHEN Ming. Design and research on energy storage and thermal power combined frequency modulation systems[J]. Huadian Technology, 2020,42(4):72-76.
[87]	彭维珂, 聂椿明, 陈衡, 等. 基于智能算法的空冷火电机组负荷预测研究[J]. 华电技术, 2021,43(3):57-64.
	PENG Weike, NIE Chunming, CHEN Heng, et al. Study on load forecasting for air cooling thermal power units based on intelligent algorithm[J]. Huadian Technology, 2021,43(3):57-64.