Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

Error Analysis of Ultra Short Term Wind Power Prediction Model

Authors
Xiaofan Zhu, Xiaoming Zha, Liang Qin
Corresponding Author
Xiaofan Zhu
Available Online March 2017.
DOI
https://doi.org/10.2991/ifmca-16.2017.116How to use a DOI?
Keywords
Error distribution; Sectional exponential distribution; Parameter estimation
Abstract
In this paper, we use a piecewise exponential distribution model to predict the ultra short term wind power error and then estimate the parameters. The case we used is from Northern Ireland, we forecast the probability and precision of wind power on the basis of Normal distribution model, Laplace distribution model, Cauchy distribution model, Beta distribution model and the proposed piecewise exponential distribution model. The prediction error distribution model of the sub index wind power forecasting error can be used to mine the relative information of the actual error distribution, in addition, it's convenient to implement and easy to be used in calculus, it can be applied to describe the error distribution of the multiple time scale prediction, so it has more advantages in the error analysis.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Volume Title
Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
978-94-6252-307-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/ifmca-16.2017.116How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xiaofan Zhu
AU  - Xiaoming Zha
AU  - Liang Qin
PY  - 2017/03
DA  - 2017/03
TI  - Error Analysis of Ultra Short Term Wind Power Prediction Model
BT  - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
PB  - Atlantis Press
SP  - 747
EP  - 752
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifmca-16.2017.116
DO  - https://doi.org/10.2991/ifmca-16.2017.116
ID  - Zhu2017/03
ER  -