Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

Short Term Power load Forecasting Considering Meteorological Factors

Authors
Jing Luo
Corresponding Author
Jing Luo
Available Online June 2016.
DOI
https://doi.org/10.2991/mecs-17.2017.27How to use a DOI?
Keywords
Short-term power load forecasting, Meteorological factors, Principal component regression analysis.
Abstract
To forecast short-term power load, we first establish GM (1, 1) grey forecasting model and test the correlation of the predicted values. Considering the impact of meteorological factors on modern power system, we establish a load forecasting model based on principal component analysis and multiple linear regression analysis. Then we compare the two kinds of load forecasting model by the precision of curve fitting with the actual load. The results show that the accurate of short-term load forecasting model included in meteorological factors is higher, we also introduce an assessment standard to provide evidence.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-352-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/mecs-17.2017.27How 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  - Jing Luo
PY  - 2016/06
DA  - 2016/06
TI  - Short Term Power load Forecasting Considering Meteorological Factors
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.27
DO  - https://doi.org/10.2991/mecs-17.2017.27
ID  - Luo2016/06
ER  -