Short Term Power load Forecasting Considering Meteorological Factors

DOI

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.

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/).

Download article (PDF)

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  - 10.2991/mecs-17.2017.27
ID  - Luo2016/06
ER  -