电力建设2017，Vol.38Issue(7)：18-24,7.DOI:10.3969/j.issn.1000-7229.2017.07.003
基于改进马尔科夫链的风电功率时间序列模型
Wind Power Time Series Model Based on Improved Markov Chain
赵宇 1肖白 1顾兵 1王逍祎 1张钰 1王成龙1
作者信息
- 1. 东北电力大学,吉林省吉林市 132000
- 折叠
摘要
Abstract
The simulation of wind power time series is of great significance in the planning and evaluation of wind power grid-connected systems.In order to solve the problem that the original Markov chain can not keep its autocorrelation in wind power modeling, this paper constructs a wind power time series model based on improved Markov chain.This paper firstly analyzes the seasonal characteristics, daily characteristics and fluctuation characteristics of wind power;and then subdivides the wind power data according to different months and time periods to generate the corresponding state transition probability matrix.Finally, this paper fits the probability distribution of wind power fluctuation and increase the amount of fluctuation to establish the wind power time series model based on improved Markov chain.The case analysis shows that the wind power series generated by the proposed model is superior to the existing model in the aspects of general statistical parameters, probability density distribution and autocorrelation, while preserving the historical sequence autocorrelation.关键词
马尔科夫链/风电功率/时间序列模拟/波动特性Key words
Markov chain/wind power/time series simulation/fluctuation characteristics分类
信息技术与安全科学引用本文复制引用
赵宇,肖白,顾兵,王逍祎,张钰,王成龙..基于改进马尔科夫链的风电功率时间序列模型[J].电力建设,2017,38(7):18-24,7.
