Generation of wind power time series to fit time-domain characteristics

Author

Jinghua Li ; Jinyu Wen ; Jiaming Li ; Shijie Cheng ; Peng Yu ; Weihua Luo

Author_Institution

Sch. of Electr. & Electron. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China

Volume

50

Issue

23

fYear

2014

fDate

11 6 2014

Firstpage

1734

Lastpage

1736

Abstract

The generation of wind power time series is important for electric power system planning and decision making. A method to generate a synthetic series of wind power outputs is proposed, considering the state transition, the duration time and the variation features of wind power. The simulation results using the proposed method for 25 wind farms at six different locations in different countries show that the wind power time series generated by the proposed method are able to reflect more comprehensive wind power characteristics than that generated by the conventional Markov chain Monte Carlo (MCMC) method.

Keywords

Markov processes; Monte Carlo methods; decision making; power generation planning; time series; time-domain analysis; wind power plants; MCMC; Markov chain Monte Carlo method; SDV features; decision making; electric power system planning; state transition duration time and the variation features; synthetic series; time-domain characteristics; wind farms; wind power time series generation;

fLanguage

English

Journal_Title

Electronics Letters

Publisher

iet

ISSN

0013-5194

Type

jour

DOI

10.1049/el.2014.1908

Filename

6955030