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1.纽约州立大学石溪分校电气与计算机系,纽约 11794,美国
2.西安交通大学电气工程学院,陕西省西安市 710049
林超凡(1995—),男,博士,主要研究方向:电力系统不确定性分析、弹性电力系统。E-mail:chaofan.lin@stonybrook.edu
别朝红(1970—),女,通信作者,博士,教授,博士生导师,主要研究方向:弹性电力系统、电力系统规划与可靠性评估。E-mail:zhbie@xjtu.edu.cn
收稿:2024-01-31,
修回:2024-05-21,
网络出版:2024-09-13,
纸质出版:2024-10-10
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林超凡,别朝红.新型电力系统不确定性静态建模及量化分析方法评述[J].电力系统自动化,2024,48(19):14-27.
LIN Chaofan,BIE Zhaohong.Review of Static Modeling and Quantitative Analysis Methods for Uncertainties of New Power Systems[J].Automation of Electric Power Systems,2024,48(19):14-27.
林超凡,别朝红.新型电力系统不确定性静态建模及量化分析方法评述[J].电力系统自动化,2024,48(19):14-27. DOI: 10.7500/AEPS20240131002.
LIN Chaofan,BIE Zhaohong.Review of Static Modeling and Quantitative Analysis Methods for Uncertainties of New Power Systems[J].Automation of Electric Power Systems,2024,48(19):14-27. DOI: 10.7500/AEPS20240131002.
中国正处在新型电力系统建设的加速转型期。新型电力系统在源网荷侧呈现的强不确定性发展趋势以及其高维度、强相关、多样化特点给传统的不确定性建模及分析方法带来挑战。文中围绕新型电力系统不确定性静态建模及量化分析方法展开评述。首先,梳理不确定性静态建模和量化分析的基本概念和框架;然后,以近几年文献调研为基础,重点从先验不确定性和后验不确定性的视角对不确定性静态建模方法进行整理和评述,以及从模型驱动和数据驱动两个层面对不确定性量化分析方法及其应用场景加以归纳和总结;最后,结合调研结果展望了未来新型电力系统不确定性静态建模和量化分析方法,指出应着力提高建模和分析方法的广度、计算效率、计算准确度并推动实际应用。
China is currently undergoing an accelerated transformation period in the construction of new power systems. The development trend of strong uncertainty on the source
grid
and load sides of new power systems and their characteristics of high-dimension
strong correlation
and diversity bring challenges to the traditional modeling and analysis methods for uncertainties. This paper reviews the static modeling and quantitative analysis methods for uncertainties of new power systems. First
the basic concepts and framework of the static modeling and quantitative analysis for uncertainties are introduced. Then
based on the literature survey in recent years
the static modeling methods for uncertainties are classified and reviewed from the perspectives of prior and posterior uncertainties
and the quantitative analysis methods for uncertainties as well as their application scenarios are categorized and summarized from two levels: model-driven and data-driven. Finally
combined with the survey results
the static modeling and quantitative analysis methods for uncertainties of future new power systems are prospected
pointing out that efforts should be made to improve the scope
calculation efficiency
and calculation accuracy
and to promote practical applications.
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