基于两阶段聚类和MCMC算法的风光出力序列建模方法

郭红霞; 邹桂林; 王子强; 陈凌轩; 马骞; 陈亦平

doi:10.19912/j.0254-0096.tynxb.2023-1473

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太阳能学报 ›› 2025, Vol. 46 ›› Issue (1) : 491-502. DOI: 10.19912/j.0254-0096.tynxb.2023-1473

基于两阶段聚类和MCMC算法的风光出力序列建模方法

郭红霞¹, 邹桂林¹, 王子强², 陈凌轩¹, 马骞², 陈亦平²

作者信息 +

A MODELING METHOD FOR WIND AND SOLAR POWER SERIES BASED ON A TWO-STAGE CLUSTERING AND MCMC ALGORITHM

Guo Hongxia¹, Zou Guilin¹, Wang Ziqiang², Chen Lingxuan¹, Ma Qian², Chen Yiping²

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文章历史 +

摘要

针对风光出力的随机性建模问题,提出一种基于两阶段聚类和双层马尔科夫链模型的风光相关出力序列建模方法。首先采用两阶段聚类得到不同的风光典型日出力模式,第1阶段采用自组织映射聚类方法识别不同气象条件下的光伏出力类型;第2阶段采用近邻传播聚类方法对不同光伏出力类型对应的风电出力样本进行聚类。其次,建立双层马尔科夫链模型描述风光出力的相依变化,上层建立单变量马尔科夫链模型描述风光出力模式的日间转移,下层建立双变量马尔科夫链模型描述风光出力日内相邻时刻的状态转移。最后,采用MCMC模拟方法得到指定时间长度的风光出力序列。仿真算例表明,所提方法在各项评价指标上均优于传统MCMC方法及Copula模型,能生成更符合风光实际相关性的出力序列。

Abstract

In time series production simulation of wind-solar power systems, generating wind-solar output sequences with temporal and spatial correlation characteristics is crucial for improving the reliability of production simulation and guiding the planning and operation of power systems. A method is proposed to address the stochastic modeling problem of wind-solar output. It involves modeling wind-solar-related output sequences using a two-stage clustering and a two-layer Markov chain model. Different wind and solar typical daily output patterns are initially obtained through a two-stage clustering process. In the first stage, a self-organized mapping clustering method is used to identify solar output patterns under various meteorological conditions. The second stage utilizes the affinity propagation clustering method to group the wind power output samples that correspond to different solar output patterns. Secondly, a two-layer Markov chain model is constructed to depict the interdependent variations in wind-solar power output. A univariate Markov chain model is developed in the upper layer to illustrate the day-to-day transition of the wind-solar power pattern, while a bivariate Markov chain model is established in the lower layer to depict the state transition of the neighboring moments of the wind-solar power within the intraday. Finally, the MCMC simulation method is used to generate the wind-solar power sequence for a specified duration. The simulation example demonstrates that the proposed method outperforms the traditional MCMC method and Copula model in all evaluation indicators. It can generate a power output sequence that more accurately reflects the actual correlation between wind and solar.

导出引用

郭红霞, 邹桂林, 王子强, 陈凌轩, 马骞, 陈亦平. 基于两阶段聚类和MCMC算法的风光出力序列建模方法[J]. 太阳能学报. 2025, 46(1): 491-502 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1473

Guo Hongxia, Zou Guilin, Wang Ziqiang, Chen Lingxuan, Ma Qian, Chen Yiping. A MODELING METHOD FOR WIND AND SOLAR POWER SERIES BASED ON A TWO-STAGE CLUSTERING AND MCMC ALGORITHM[J]. Acta Energiae Solaris Sinica. 2025, 46(1): 491-502 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1473

中图分类号： TM743

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