Study on optimized operation model and strategy for virtual power plants considering multi-energy coupling

doi:10.3969/j.issn.2097-0706.2025.01.005

Abstract

Abstract:

An optimized operation model for virtual power plants（VPPs），which considers the multi-energy coupling characteristics of energy parks，is proposed to address issues like energy supply-demand imbalance and operational inefficiency caused by large-scale integration of renewable energy into the power grid. First，the basic concept of a VPP tailored for a multi-energy coupling park was introduced. Then，a power balance model for various energy systems within the VPP was developed，taking into account both multi-energy economic operations and renewable energy consumption needs within the park. Building upon this power balance model，an optimal operation model for a multi-energy coupled VPP was formulated，utilizing mixed integer linear programming for solving the model. Finally，simulations were conducted on the VPP incorporating multi-energy coupling equipment，demonstrating that this optimized model significantly enhanced the comprehensive utilization efficiency of heterogeneous energy sources，reduced operational costs，and improved the rate of renewable energy consumption.

Key words: virtual power plant（VPP）, multi-energy coupling, optimized operation, local consumption, "dual carbon" target, total operating cost, renewable energy consumption

CLC Number:

TK01

JIANG Yan, SONG Chenhui, ZHANG Ning, HE Bo, LU Yuting. Study on optimized operation model and strategy for virtual power plants considering multi-energy coupling[J]. Integrated Intelligent Energy, 2025, 47(1): 34-41.

Figures/Tables 11

Fig.1

Fig.2

Table 1

Table 2

Table 3

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

References 28

[1]	李政, 陈思源, 董文娟, 等. 碳约束条件下电力行业低碳转型路径研究[J]. 中国电机工程学报, 2021, 41(12): 3987-4001.
	LI Zheng, CHEN Siyuan, DONG Wenjuan, et al. Low carbon transition pathway of power sector under carbon emission constraints[J]. Proceedings of the CSEE, 2021, 41(12): 3987-4001.
[2]	黎博, 陈民铀, 钟海旺, 等. 高比例可再生能源新型电力系统长期规划综述[J]. 中国电机工程学报, 2023, 43(2): 555-581.
	LI Bo, CHEN Minyou, ZHONG Haiwang, et al. A review of long-term planning of new power systems with large share of renewable energy[J]. Proceedings of the CSEE, 2023, 43(2): 555-581.
[3]	解蛟龙. 风/光/负荷典型场景缩减方法及在电网规划中的应用[D]. 合肥: 合肥工业大学, 2017.
	XIE Jiaolong. Wind/light/load typical scene reduction method and its application in power grid planning[D]. Hefei: Hefei University of Technology, 2017.
[4]	裴佑楠. 考虑灵活性的电力系统动态经济调度理论研究[D]. 济南: 山东大学, 2023.
	PEI Younan. Theoretical study on dynamic economic dispatch of power system considering flexibility[D]. Jinan: Shandong University, 2023.
[5]	张高. 含多种分布式能源的虚拟电厂竞价策略与协调调度研究[D]. 上海: 上海交通大学, 2019.
	ZHANG Gao. Research on bidding strategy and coordinated scheduling of virtual power plant with multiple distributed energy sources[D]. Shanghai: Shanghai Jiao Tong University, 2019.
[6]	孙强, 谢典, 聂青云, 等. 含电-热-冷-气负荷的园区综合能源系统经济优化调度研究[J]. 中国电力, 2020, 53(4): 79-88.
	SUN Qiang, XIE Dian, NIE Qingyun, et al. Research on economic optimization scheduling of park integrated energy system with electricity-heat-cool-gas load[J]. Electric Power, 2020, 53(4): 79-88.
[7]	梁安琪, 曾爽, 任佳航, 等. 基于博弈优化算法的综合电热协同网络中热泵系统的智能化运行动态特性研究[J]. 制冷学报, 2024, 45(2): 109-118.
	LIANG Anqi, ZENG Shuang, REN Jiahang, et al. Intelligent operation dynamic characteristics of heat pump system in integrated electric-thermal cooperative grid based on game optimization algorithm[J]. Journal of Refrigeration, 2024, 45(2): 109-118.
[8]	王京龙, 王晖, 杨野, 等. 考虑多重不确定性的电-热-气综合能源系统协同优化方法[J]. 综合智慧能源, 2024, 46(4): 42-51. doi: 10.3969/j.issn.2097-0706.2024.04.006
	WANG Jinglong, WANG Hui, YANG Ye, et al. Collaborative optimization method for power-heat-gas integrated energy systems considering multiple uncertainties[J]. Integrated Intelligent Energy, 2024, 46(4): 42-51. doi: 10.3969/j.issn.2097-0706.2024.04.006
[9]	黄大为, 史博铭, 于娜, 等. 热电联产机组利用热网动态特性提升实时灵活性的自调度策略[J/OL]. 中国电机工程学报, 2024: 1-13(2024-04-30)[2024-08-30].DOI:10.13334/j.0258-8013.pcsee.240168.
	HUANG Dawei, SHI Boming, YU Na, et al. Self-scheduling Strategy to improve the real-time flexibility of CHP unit by utilizing heat network dynamic characteristics[J]. Proceedings of the CSEE, 2024:1-13(2024-04-30)[2024-08-30].DOI:10.13334/j.0258-8013.pcsee.240168.
[10]	王艳松, 王毓铎. 计及电制氢和碳捕集的园区综合能源系统动态规划[J]. 中国石油大学学报(自然科学版), 2024, 48(2): 142-150.
	WANG Yansong, WANG Yuduo. Dynamic programming of park-level integrated energy system considering electricity hydrogen production and carbon capture[J]. Journal of China University of Petroleum (Edition of Natural Science), 2024, 48(2): 142-150.
[11]	孙诗洁. 考虑工业负荷生产特性的虚拟电厂优化调度与储能配置研究[D]. 杭州: 浙江大学, 2023.
	SUN Shijie. Research on optimal scheduling and energy storage configuration of virtual power plant considering the production characteristics of industrial load[D]. Hangzhou: Zhejiang University, 2023.
[12]	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, 7069.
	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, 7069.
[13]	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.
[14]	YANG H L, TIAN X, LIU F, et al. A multi-objective dispatching model for a novel virtual power plant considering combined heat and power units, carbon recycling utilization, and flexible load response[J/OL]. Frontiers in Energy Research:1-16(2024-08-02)[2024-08-30]. https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2023.1332474/pdf.
[15]	SONG M, XU X Y, GAO C W, et al. Two-stage stochastic scheduling of virtual power plant based on transactive control[J]. CSEE Journal of Power and Energy Systems, 2023, 152: 109235.
[16]	郁海彬, 卢闻州, 唐亮, 等. 考虑风险偏好的多主体虚拟电厂经济调度与收益分配策略[J]. 综合智慧能源, 2024, 46(6): 66-77. doi: 10.3969/j.issn.2097-0706.2024.06.008
	YU Haibin, LU Wenzhou, TANG Liang, et al. Economic dispatch and profit distribution strategy for multi-agent virtual power plants considering risk preferences[J]. Integrated Intelligent Energy, 2024, 46(6): 66-77. doi: 10.3969/j.issn.2097-0706.2024.06.008
[17]	田泽禹, 沙钊旸, 赵全斌, 等. 针对温控负载变化的虚拟电厂控制策略研究[J]. 综合智慧能源, 2024, 46(1): 28-37. doi: 10.3969/j.issn.2097-0706.2024.01.004
	TIAN Zeyu, SHA Zhaoyang, ZHAO Quanbin, et al. Research on control strategy for virtual power plants in response to thermostatically controlled loads[J]. Integrated Intelligent Energy, 2024, 46(1): 28-37. doi: 10.3969/j.issn.2097-0706.2024.01.004
[18]	李明扬, 窦梦园. 基于强化学习的含电动汽车虚拟电厂优化调度[J]. 综合智慧能源, 2024, 46(6): 27-34. doi: 10.3969/j.issn.2097-0706.2024.06.004
	LI Mingyang, DOU Mengyuan. Optimal scheduling of virtual power plants integrating electric vehicles based on reinforcement learning[J]. Integrated Intelligent Energy, 2024, 46(6): 27-34. doi: 10.3969/j.issn.2097-0706.2024.06.004
[19]	左娟, 艾芊, 王帝, 等. 面向虚拟电厂的电力调峰市场隐私保护交易策略[J]. 电力系统自动化, 2024, 48(18):149-157.
	ZUO Juan, AI Qian, WANG Di, et al. Privacy-preserving trading strategies for virtual power plants in power peaking market[J]. Power System Automation, 2024, 48(18):149-157.
[20]	任帅, 肖楚鹏, 梁新龙, 等. 计及虚拟电厂内需求侧灵活性资源的实时电价和V2G协调优化调度策略[J]. 电力信息与通信技术, 2024, 22(8): 27-36.
	REN Shuai, XIAO Chupeng, LIANG Xinlong, et al. The real-time electricity price and V2G coordinated optimal scheduling strategy considering demand-side flexibility resources in VPP[J]. Electric Power Information and Communication Technology, 2024, 22(8): 27-36.
[21]	刘宏亮, 李琦, 程雅雯, 等. 计及分时电价的风光氢储互补综合系统日前优化调度[J]. 东北电力技术, 2023, 44(7):1-6.
	LIU Hongliang, LI Qi, CHENG Yawen, et al. Day-ahead optimal scheduling of wind-solar-hydrogen-storage complementary integrated system with time-of-use electricity price[J]. Northeast Electric Power Technology, 2023, 44(7):1-6.
[22]	王飞, 王歌, 徐飞. 面向系统响应能力提升的虚拟电厂聚合特性及交易机制综述[J]. 电力系统自动化, 2024, 48(18):87-103.
	WANG Fei, WANG Ge, XU Fei. A review of virtual power plant aggregation characteristics and transaction mechanism for system responsiveness improvement[J]. Power system automation, 2024, 48(18):87-103.
[23]	董朝阳, 赵俊华, 文福拴, 等. 从智能电网到能源互联网: 基本概念与研究框架[J]. 电力系统自动化, 2014, 38(15): 1-11.
	DONG Zhaoyang, ZHAO Junhua, WEN Fushuan, et al. From smart grid to energy Internet: Basic concept and research framework[J]. Automation of Electric Power Systems, 2014, 38(15): 1-11.
[24]	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.
[25]	胡洋, 董治新, 韩雅萱, 等. 促进新能源消纳的虚拟电厂运营优化策略[J]. 科技管理研究, 2024, 44(14): 173-182.
	HU Yang, DONG Zhixin, HAN Yaxuan, et al. Operation optimization strategy of virtual power plants for promoting new energy consumption[J]. Science and Technology Management Research, 2024, 44(14): 173-182.
[26]	蒋超凡, 艾欣. 计及多能耦合机组不确定性的综合能源系统运行优化模型研究[J]. 电网技术, 2019, 43(8): 2843-2854.
	JIANG Chaofan, AI Xin. Integrated energy system operation optimization model considering uncertainty of multi-energy coupling units[J]. Power System Technology, 2019, 43(8): 2843-2854.
[27]	门向阳, 曹军, 王泽森, 等. 能源互联微网型多能互补系统的构建与储能模式分析[J]. 中国电机工程学报, 2018, 38(19): 5727-5737, 5929.
	MEN Xiangyang, CAO Jun, WANG Zesen, et al. The constructing of multi-energy complementary system of energy Internet microgrid and energy storage model analysis[J]. Proceedings of the CSEE, 2018, 38(19): 5727-5737, 5929.
[28]	吴雄, 王秀丽, 王建学, 等. 微网经济调度问题的混合整数规划方法[J]. 中国电机工程学报, 2013, 33(28): 1-9.
	WU Xiong, WANG Xiuli, WANG Jianxue, et al. economic generation scheduling of a microgrid using mixed integer programming[J]. Proceedings of the CSEE, 2013, 33(28): 1-9.

时段		购电电价
低电价时段	00:00 — 06:00，22:00 — 24:00	0.54
平电价时段	06:00 — 08:00，11:00 —17:00	0.74
高电价时段	08:00 —11:00，17:00 —22:00	0.88

设备	参数	数值
燃气轮机	发电效率/热损失率/余热回收率/余热回收制热效率/余热分流制热/制冷占比	0.35/0.20/ 0.50/0.95/0.45/0.55
吸收式制冷机	制冷系数	0.80
燃气锅炉	制热效率	0.90
电制冷机	制冷系数	2.50
电锅炉	制热效率	0.95