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1.清华大学电机工程与应用电子技术系,北京市 100084
2.新型电力系统运行与控制全国重点实验室(清华大学),北京市100084
3.南方电网科学研究院有限责任公司,广东省广州市 510663
Received:04 August 2023,
Revised:2024-02-01,
Published Online:07 May 2024,
Published:10 June 2024
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张帅龙,郑可迪,刘学等.基于藤Copula理论的海上风电建模及电力市场运行分析[J].电力系统自动化,2024,48(11):134-142.
ZHANG Shuailong,ZHENG Kedi,LIU Xue,et al.Modeling of Offshore Wind Power Based on Vine Copula Theory and Electricity Market Operation Analysis[J].Automation of Electric Power Systems,2024,48(11):134-142.
张帅龙,郑可迪,刘学等.基于藤Copula理论的海上风电建模及电力市场运行分析[J].电力系统自动化,2024,48(11):134-142. DOI: 10.7500/AEPS20230804004.
ZHANG Shuailong,ZHENG Kedi,LIU Xue,et al.Modeling of Offshore Wind Power Based on Vine Copula Theory and Electricity Market Operation Analysis[J].Automation of Electric Power Systems,2024,48(11):134-142. DOI: 10.7500/AEPS20230804004.
海上风电因具有更高的发电利用小时数,将成为中国实现“碳中和·碳达峰”的重要技术选项。随着海上风电装机容量的不断提升,其出力的间歇性、波动性将对电力系统的安全稳定和电力市场的经济运行造成显著影响。为刻画不同站点间风速的相关性,基于藤Copula理论对海上风电的出力进行建模,并利用C藤Copula函数构建多风电场出力的联合分布模型。在此基础上,提出基于共识聚类的电力市场典型阻塞场景构建方法,并采用简化的中国广东省电网架构数据开展算例仿真计算,对大规模海上风电并网前后电力系统的发电结构、碳排放量、市场电价等关键指标的变化进行实证分析。
Offshore wind power will become an important technological option for China to achieve carbon emission peak and carbon neutrality due to its more utilization hours for electric power generation. However
with the continuous increase in the offshore wind power installed capacity
its intermittency and fluctuation will have a significant impact on the security and stability of power systems
as well as the economic operation of electricity markets. To characterize the correlation between wind speeds at different station sites
the vine copula theory is used for offshore wind power modeling and a joint distribution model is constructed for multiple wind farms by using the C-vine copula function. On this basis
a method is proposed for constructing the typical congestion scenarios in the electricity market based on the consensus clustering. Numerical simulation calculations are conducted with the simplified power grid architecture data of Guangdong province
China to empirically analyze the changes in key indicators such as generation structure of the power system
carbon emissions
and market electricity prices before and after the large-scale grid-integration of offshore wind power.
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