Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)

A solar energy resources estimation method based on EOF and ARMA model

Authors
Qiang Zhou, Libin Yang, Hai Zhou, Jie Ding
Corresponding Author
Qiang Zhou
Available Online November 2016.
DOI
10.2991/aest-16.2016.15How to use a DOI?
Keywords
EOF; ARMA model; solar energy; resources calculation.
Abstract

A method to estimate solar energy resources was introduced in this paper. Based on the solar data observed by meteorological stations, the temporal-spatial characteristics of solar energy resources in the west of China were analysed by EOF. The main modal was determined and its time series was forecasted by ARMA model. Using the time series forecasted by ARMA model and the space factors of observed data computed by EOF, the prediction of solar resources field was estimated. Experiment results show that the predicted field tends to reflect the characteristics of the measured field and the area of solar energy resources can be estimated by this method properly.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
10.2991/aest-16.2016.15
ISSN
1951-6851
DOI
10.2991/aest-16.2016.15How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Qiang Zhou
AU  - Libin Yang
AU  - Hai Zhou
AU  - Jie Ding
PY  - 2016/11
DA  - 2016/11
TI  - A solar energy resources estimation method based on EOF and ARMA model
BT  - Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)
PB  - Atlantis Press
SP  - 118
EP  - 123
SN  - 1951-6851
UR  - https://doi.org/10.2991/aest-16.2016.15
DO  - 10.2991/aest-16.2016.15
ID  - Zhou2016/11
ER  -