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1.中国南方电网有限责任公司,广东省广州市 510663
2.中国能源建设集团广东省电力设计研究院有限公司,广东省广州市 510663
Received:01 November 2022,
Revised:2023-03-16,
Published Online:30 May 2023,
Published:10 August 2023
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辛阔,马骞,许琴等.基于月份划分与指定日类型的风电出力序列场景生成方法[J].电力系统自动化,2023,47(15):151-161.
XIN Kuo,MA Qian,XU Qin,et al.Wind Power Output Sequence Scenario Generation Method Based on Monthly Division and Specified Day Type[J].Automation of Electric Power Systems,2023,47(15):151-161.
辛阔,马骞,许琴等.基于月份划分与指定日类型的风电出力序列场景生成方法[J].电力系统自动化,2023,47(15):151-161. DOI: 10.7500/AEPS20221101006.
XIN Kuo,MA Qian,XU Qin,et al.Wind Power Output Sequence Scenario Generation Method Based on Monthly Division and Specified Day Type[J].Automation of Electric Power Systems,2023,47(15):151-161. DOI: 10.7500/AEPS20221101006.
风电场景生成是不确定性条件下进行电网调度及安全校核的重要基础。文中提出一种风电出力序列场景生成方法。首先,基于月均出力将年度风电出力序列划分为分布特性差异大的数个季度;然后
基于风电出力的日特性指标,对年度风电出力序列进行典型日聚类分析,并构建各日类型下的日特性指标联合分布函数。接着,用马尔可夫链描述每一季度内的日类型转移特性,并基于此通过抽样获得未来一段时期内每一日的日类型及日特性指标。进而采用优化技术生成未来一段时间内每日96点日风电出力序列。文中进一步提出了可根据指定极端日类型、日期位置以及长度的风电出力序列场景生成新方法。最后,通过算例分析证明了所提方法的有效性和可行性。
Wind power scenario generation is an important basis for power grid dispatching and security checking under uncertain conditions. In this paper
a wind power output sequence scenario generation method is proposed. Firstly
based on the average monthly power output
the annual wind power series are divided into several quarters with large differences in distribution characteristics. Secondly
based on the daily characteristic indices of wind power output
the typical-day cluster analysis is carried out based on the annual wind power output sequence
and the joint distribution function of day characteristic indices for each day type is constructed. Thirdly
the Markov chain is used to describe the characteristics of day type transition in each quarter
and based on this
the types and daily characteristics of each day during the future period are obtained by sampling. Furthermore
the 96-point daily wind power output sequence of corresponding days during the future period is generated using the optimization technology. A new method for generating wind power output sequence scenarios according to the specified extreme day types
date and lengths is further proposed. Finally
the effectiveness and feasibility of the proposed method are verified by case analysis.
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