全球能源互联网（英文）2022，Vol.5Issue(1)：44-54,11.DOI:10.14171/j.2096-5117.gei.2022.01.004
基于典型日出力场景和马尔科夫算法的风电功率时间序列模拟模型
Wind power time series simulation model based on typical daily output processes and Markov algorithm
摘要
Abstract
The simulation of wind power time series is a key process in renewable power allocation planning, operation mode calculation, and safety assessment. Traditional single-point modeling methods discretely generate wind power at each moment; however, they ignore the daily output characteristics and are unable to consider both modeling accuracy and efficiency. To resolve this problem, a wind power time series simulation model based on typical daily output processes and Markov algorithm is proposed. First, a typical daily output process classification method based on time series similarity and modified K-means clustering algorithm is presented. Second, considering the typical daily output processes as status variables, a wind power time series simulation model based on Markov algorithm is constructed. Finally, a case is analyzed based on the measured data of a wind farm in China. The proposed model is then compared with traditional methods to verify its effectiveness and applicability. The comparison results indicate that the statistical characteristics, probability distributions, and autocorrelation characteristics of the wind power time series generated by the proposed model are better than those of the traditional methods. Moreover, modeling efficiency considerably improves.关键词
风电功率/时间序列/典型日出力场景/马尔科夫算法/改进K-means聚类算法Key words
Wind power/Time series/Typical daily output processes/Markov algorithm/Modified K-means clustering algorithm引用本文复制引用
丛智慧,于越聪,李林晏,阎洁..基于典型日出力场景和马尔科夫算法的风电功率时间序列模拟模型[J].全球能源互联网（英文）,2022,5(1):44-54,11.基金项目
This work was supported by the China Datang Corporation project"Study on the performance improvement scheme of in-service wind farms",the Fundamental Research Funds for the Central Universities?(2020MS021),and the Foundation of State Key Laboratory"Real-time prediction of offshore wind power and load reduction control method"(LAPS2020-07). （2020MS021）
