Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)

Short-term forecasting of the power system

Authors
Xingxuan Zhang
Corresponding Author
Xingxuan Zhang
Available Online April 2017.
DOI
10.2991/fmsmt-17.2017.185How to use a DOI?
Keywords
regression analysis, time series analysis, Short - term load forecast.
Abstract

In order to predict the short-term load of the power system, we used regression analysis and time series analysis. Firstly, We plotted the annual load curve of a region and analysed the relationship between load and each meteorological factor. Secondly, the regression model is established and the regression equation is obtained. Through the analysis, we find that the average temperature has the most obvious influence on the load. Finally, using the time series model and considering the influence of the weather, the load forecasting model of the power system is established, and the good prediction results are obtained.

Copyright
© 2017, 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 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
978-94-6252-331-9
ISSN
2352-5401
DOI
10.2991/fmsmt-17.2017.185How to use a DOI?
Copyright
© 2017, 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  - Xingxuan Zhang
PY  - 2017/04
DA  - 2017/04
TI  - Short-term forecasting of the power system
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 959
EP  - 962
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.185
DO  - 10.2991/fmsmt-17.2017.185
ID  - Zhang2017/04
ER  -