Markov chain‐based wind power time series modelling method considering the influence of the state duration on the state transition probability-Reference-Cited by-同舟云学术

Markov chain‐based wind power time series modelling method considering the influence of the state duration on the state transition probability

Published:2019-06-17 Issue:12 Volume:13 Page:2051-2061
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Generation

Author:

Zhu Chenxi¹^ORCID,Zhang Yan¹,Yan Zheng¹,Zhu Jinzhou¹

Affiliation:

1. Key Laboratory of Control of Power Transmission and ConversionMinistry of EducationDepartment of Electrical EngineeringShanghai Jiao Tong University800 Dongchuan RoadShanghaiPeople's Republic of China

Funder

National Key Research and Development Program of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2019.0064

Reference39 articles.

1. Improving supervised wind power forecasting models using extended numerical weather variables and unlabelled data

2. Short‐term wind power forecasting and uncertainty analysis using a hybrid intelligent method

3. First and second order Markov chain models for synthetic generation of wind speed time series

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