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1.电力系统及发电设备控制和仿真国家重点实验室,清华大学,北京市 100084
2.清华大学电机工程与应用电子技术系,北京市 100084
Received:27 December 2021,
Revised:2022-06-01,
Published Online:17 August 2022,
Published:10 January 2023
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郭鸿业,郑可迪,唐庆虎等.数据驱动的电力市场研究:挑战与展望[J].电力系统自动化,2023,47(1):200-215.
GUO Hongye,ZHENG Kedi,TANG Qinghu,et al.Data-driven Research on Electricity Markets: Challenges and Prospects[J].Automation of Electric Power Systems,2023,47(1):200-215.
郭鸿业,郑可迪,唐庆虎等.数据驱动的电力市场研究:挑战与展望[J].电力系统自动化,2023,47(1):200-215. DOI: 10.7500/AEPS20211227007.
GUO Hongye,ZHENG Kedi,TANG Qinghu,et al.Data-driven Research on Electricity Markets: Challenges and Prospects[J].Automation of Electric Power Systems,2023,47(1):200-215. DOI: 10.7500/AEPS20211227007.
传统意义上的电力市场研究多建立在经典、简化的经济学模型之上,采用理性人假设与理想化的博弈模型,其结果常与实际市场状态产生较大偏差。近年来,电力市场数据逐渐开放,数据驱动研究方法快速发展,数据驱动的电力市场研究逐步成为研究热点,取得了一系列的理论成果及实际应用。为此,文中尝试对数据驱动的电力市场研究进行梳理。首先,总结了传统电力市场研究的发展现状,分析其局限性;其次,介绍并比较了目前全球不同电力市场实际的信息发布与数据开放政策;进一步,对采用数据驱动技术路线开展电力市场研究的现状进行综述;最后,归纳数据驱动的电力市场研究的关键挑战,并对未来的研究方向与应用前景进行了展望。
The traditional electricity market studies are mostly based on the classical and simplified economic models
using the assumption of rational man and idealized game models. It usually causes a large deviation from the analysis results with the real situations. In recent years
with the gradual opening of various types of electricity market data and the rapid development of data-driven analysis methods
the data-driven research on electricity markets has gradually become a hotspot
and a series of theoretical improvements and practical applications have been achieved in this field. To this end
this paper attempts to review the studies on the data-driven research on electricity markets. Firstly
the development status of traditional electricity market research is summarized and its limitations are analyzed. Secondly
the actual information disclosure and data openness policies of different electricity markets around the world are introduced and compared. Thirdly
the current situation of electricity market research using data-driven analysis technology is reviewed. Finally
the key challenges of data-driven electricity market research are summarized and the future research directions and application prospects are outlined.
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