EN电力市场环境下分布式能源系统的多元运行模式与灵活性影响分析
Impacts of Diverse Operational Modes and Flexibility of Distributed Energy Systems within Electricity Market
- 中国电力 2025年58卷第11期 页码：111-121
- 作者机构：
1. 国网辽宁省电力有限公司,辽宁,沈阳,110006
2. 清华大学 电机工程与应用电子技术系,北京,100084
- 作者简介：
- 基金信息：国家重点研发计划资助项目（2021YFB2401200）。
DOI：10.11930/j.issn.1004-9649.202501049
中图分类号：-
网络出版：2025-12-01，
纸质出版：2025-12-01
- 稿件说明：
移动端阅览
宋卓然, 张燕妮, 王阳, 蒋海玮, 李嘉宇, 高洪超. 电力市场环境下分布式能源系统的多元运行模式与灵活性影响分析[J]. 中国电力, 2025, 58(11): 111-121.
SONG Zhuoran, ZHANG Yanni, WANG Yang, et al. Impacts of Diverse Operational Modes and Flexibility of Distributed Energy Systems within Electricity Market[J]. 2025, 58(11): 111-121.
宋卓然, 张燕妮, 王阳, 蒋海玮, 李嘉宇, 高洪超. 电力市场环境下分布式能源系统的多元运行模式与灵活性影响分析[J]. 中国电力, 2025, 58(11): 111-121. DOI： 10.11930/j.issn.1004-9649.202501049.
SONG Zhuoran, ZHANG Yanni, WANG Yang, et al. Impacts of Diverse Operational Modes and Flexibility of Distributed Energy Systems within Electricity Market[J]. 2025, 58(11): 111-121. DOI： 10.11930/j.issn.1004-9649.202501049.
摘要
需求侧协同能力提升是加快构建新型电力系统的关键举措之一。与传统资源不同的是，分布式资源的灵活性受限于用户有限理性及零售市场的价值传导机制，深入挖掘分布式能源系统与电网的互动模式及灵活性影响机理成为关键议题。为此，立足用户视角，首先梳理了分布式资源与电力系统的典型互动模式，剖析了用户不同行为模式的选择逻辑。然后分析了现行市场机制下资源用户可参与的市场交易模式及其对用户行为的影响机理，发现现货价格信号的直接传导将最大程度地激励资源用户的策略性行为，但用户的有限理性决策也会带来市场运营风险。为缓解这一影响，进一步提出了资源用户参与现货市场的分电量申报机制。最后基于中国某省的市场价格信号真实数据，论证了该分析方法及改进机制的合理性。
Abstract
Improving demand side collaboration capability is one of the key measures to accelerate the construction of new power systems. Unlike traditional resources
the flexibility of distributed resources is limited by the bounded rationality of users and the value transmission mechanism of the retail market. Exploring the interaction modes and flexibility impact mechanism between distributed energy systems and power grids has become a key issue. To this end
based on the user's perspective
we firstly sorted out the typical interaction modes between distributed resources and power systems
and analyzed the selection logic of users' different behavior patterns. Secondly
we analyzed the market transaction models available to resource users under current market mechanisms and their impact mechanism on users' behaviors. It was found that the direct transmission of spot price signals will maximally incentivize strategic behaviors among resource users
while their bounded rationality in decision-making simultaneously introduces operational risks to market stability. To mitigate these compounded effects
we proposed a split electricity volume bidding mechanism for resource users participating in spot markets. Finally
based on the real data of market price signals in a province in China
the rationality of the proposed method and the improved mechanism was demonstrated.
关键词
Keywords
references
2SHI M G, WANG H, XIE P, et al. Distributed energy scheduling for integrated energy system clusters with peer-to-peer energy transaction[J]. IEEE Transactions on Smart Grid, 2023, 14 (1): 142- 156. DOI
3SARMIENTO-VINTIMILLA J C, TORRES E, LARRUSKAIN D M, et al. Applications, operational architectures and development of virtual power plants as a strategy to facilitate the integration of distributed energy resources[J]. Energies, 2022, 15 (3): 775. DOI
4赵宇, 李谦, 张云晓, 等. 含分布式能源配电网中考虑供电可靠性的混合储能优化配置[J]. 智慧电力, 2024, 52 (8): 25- 32, 49. DOI
ZHAO Yu, LI Qian, ZHANG Yunxiao, et al. Optimal configuration of hybrid energy storage considering power supply reliability in distribution network with distributed energy[J]. Smart Power, 2024, 52 (8): 25- 32, 49. DOI
5孙秋野, 姚葭, 王一帆. 从虚拟电厂到真实电量: 虚拟电厂研究综述与展望[J]. 发电技术, 2023, 44 (5): 583- 601. DOI
SUN Qiuye, YAO Jia, WANG Yifan. From virtual power plant to real electricity: summary and prospect of virtual power plant research[J]. Power Generation Technology, 2023, 44 (5): 583- 601. DOI
6JING R, HUA W Q, LIN J, et al. Cost-efficient decarbonization of local energy systems by whole-system based design optimization[J]. Applied Energy, 2022, 326, 119921. DOI
7李明扬, 张智. 基于强化学习的含分布式风-光-储虚拟电厂优化调度[J]. 智慧电力, 2024, 52 (8): 50- 56. DOI
LI Mingyang, ZHANG Zhi. Optimal dispatch of distributed wind-solar-storage virtual power plants based on reinforcement learning[J]. Smart Power, 2024, 52 (8): 50- 56. DOI
8曾鸣, 彭丽霖, 孙静惠, 等. 兼容需求侧可调控资源的分布式能源系统经济优化运行及其求解算法[J]. 电网技术, 2016, 40 (6): 1650- 1656.
ZENG Ming, PENG Lilin, SUN Jinghui, et al. Economic optimization and corresponding algorithm for distributed energy system compatible with demand-side resources[J]. Power System Technology, 2016, 40 (6): 1650- 1656.
9朱茳, 王海潮, 赵振宇, 等. 大规模分布式能源博弈竞争模型及其求解算法[J]. 电力建设, 2017, 38 (4): 135- 143. DOI
ZHU Jiang, WANG Haichao, ZHAO Zhenyu, et al. Game competition model of large-scale distributed energy system and its solution algorithm[J]. Electric Power Construction, 2017, 38 (4): 135- 143. DOI
10LIU X, HUANG T, QIU H F, et al. Optimal aggregation of a virtual power plant based on a distribution-level market with the participation of bounded rational agents[J]. Applied Energy, 2024, 364, 123196. DOI
11高洪超, 王宣元, 邱小燕, 等. 新型电力系统环境下的虚拟电厂辅助调峰市场机制及其商业模式设计[J]. 太阳能学报, 2023, 44 (3): 376- 385.
GAO Hongchao, WANG Xuanyuan, QIU Xiaoyan, et al. Ramping energy market mechanism and its business model of virtual power plants oriented to new power system[J]. Acta Energiae Solaris Sinica, 2023, 44 (3): 376- 385.
12AMPATZIS M, NGUYEN P H, KLING W. Local electricity market design for the coordination of distributed energy resources at district level[C]//IEEE PES Innovative Smart Grid Technologies, Europe. Istanbul, Turkey. IEEE, 2014: 1–6.
13HAIDER R, D'ACHIARDI D, VENKATARAMANAN V, et al. Reinventing the utility for distributed energy resources: a proposal for retail electricity markets[J]. Advances in Applied Energy, 2021, 2, 100026. DOI
14温亚东. 新型电力系统背景下蒙西电力市场分布式能源交易机制分析[J]. 内蒙古电力技术, 2023, 41 (3): 78- 85.
WEN Yadong. Analysis on distributed energy trading mechanism in west Inner Mongolia power market under background of new power system[J]. Inner Mongolia Electric Power, 2023, 41 (3): 78- 85.
15蒋莉萍, 李琼慧, 黄碧斌, 等. 中国分布式电源与微电网发展前景及实现路径[M]. 北京: 中国电力出版社, 2017.
17国家发展改革委经济运行调节局, 国家电网公司营销部, 南方电网公司市场营销部. 分布式能源与热电冷联产[M]. 北京: 中国电力出版社, 2013.
18尤海侠. 考虑隔墙售电模式和碳排放权交易的分布式光伏项目经济性分析[J]. 能源研究与信息, 2022, 38 (4): 203- 209.
YOU Haixia. Economic analysis of distributed photovoltaic projects considering short-circuits distributed-power trading mode and carbon emissions trading[J]. Energy Research and Information, 2022, 38 (4): 203- 209.
19陈奇芳, 李若凡, 夏明超, 等. 计及多维性能评估的新型配电网光伏选址定容方法[J]. 中国电力, 2024, 57 (10): 172- 178.
CHEN Qifang, LI Ruofan, XIA Mingchao, et al. Photovoltaic site selection and capacity determination method for new distribution network considering multidimensional performance evaluation[J]. Electric Power, 2024, 57 (10): 172- 178.
20国家能源局. 关于支持电力领域新型经营主体创新发展的指导意见(国能发法改〔2024〕93号)[Z].
21成润婷, 张勇军, 李立浧, 等. 面向高比例可再生能源消纳的电力市场建设及研究进展[J]. 中国工程科学, 2023, 25 (2): 89- 99.
CHENG Runting, ZHANG Yongjun, LI Licheng, et al. Construction and research progress of electricity market for high-proportion renewable energy consumption[J]. Strategic Study of CAE, 2023, 25 (2): 89- 99.
22陈启鑫, 房曦晨, 郭鸿业, 等. 电力现货市场建设进展与关键问题[J]. 电力系统自动化, 2021, 45 (6): 3- 15. DOI
CHEN Qixin, FANG Xichen, GUO Hongye, et al. Progress and key issues for construction of electricity spot market[J]. Automation of Electric Power Systems, 2021, 45 (6): 3- 15. DOI
23庄晓丹, 刘卫东, 黄为群, 等. 浙江电力现货市场环境下储能的市场交易机制与效益分析[J]. 中国电力, 2022, 55 (6): 80- 85.
ZHUANG Xiaodan, LIU Weidong, HUANG Weiqun, et al. Energy storage market trading mechanism and benefit analysis of Zhejiang power spot market[J]. Electric Power, 2022, 55 (6): 80- 85.
24广东电力交易中心. 关于广东电力市场2024年度零售交易及合同签订情况的通告(广东交易〔2024〕1号)[Z].
25傅旭, 李富春, 杨欣, 等. 基于全寿命周期成本的储能成本分析[J]. 分布式能源, 2020, 5 (3): 34- 38.
FU Xu, LI Fuchun, YANG Xin, et al. Cost analysis of energy storage based on life cycle cost[J]. Distributed Energy, 2020, 5 (3): 34- 38.
26徐岩, 何宸, 付超, 等. 多种调度模式下的光储电站经济性最优储能容量配置分析[J]. 太阳能学报, 2019, 40 (6): 1632- 1640.
XU Yan, HE Chen, FU Chao, et al. Analysis of energy storage capacity allocation considering optimal economy of pv & battery cogeneration system under different scheduling modes[J]. Acta Energiae Solaris Sinica, 2019, 40 (6): 1632- 1640.
27崔杨, 安宁, 付小标, 等. 面向高比例新能源电力系统调峰需求的储能容量配置方法综述[J]. 东北电力大学学报, 2023, 43 (1): 1- 8.
CUI Yang, AN Ning, FU Xiaobiao, et al. Overview of energy storage capacity allocation methods for high-proportion new energy power system peak shaving demand[J]. Journal of Northeast Electric Power University, 2023, 43 (1): 1- 8.
28康渭滨, 寇明鑫, 张文文, 等. 光伏储能电站不同储能形式经济性对比分析[J]. 电力科技与环保, 2024, 40 (3): 276- 285.
KANG Weibin, KOU Mingxin, ZHANG Wenwen, et al. Economic comparison analysis of different energy storage forms for photovoltaic energy storage power stations[J]. Electric Power Technology and Environmental Protection, 2024, 40 (3): 276- 285.
29PAN C C, JIN T, LI N, et al. Multi-objective and two-stage optimization study of integrated energy systems considering P2G and integrated demand responses[J]. Energy, 2023, 270, 126846. DOI
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