Power system short-term load forecasting

DOI

10.2991/icmmct-17.2017.49How to use a DOI?

Keywords

Short-term load forecasting, Multiple linear regression, Residual standard deviation

Abstract

In modern power system, the influence of meteorological factors on the load is increasingly prominent. In order to make the decision-making in power system more scientific, we should consider the meteorological factors, to improve the short-term load forecasting accuracy. Due to the weather factors influencing the load are multiple, with the method of multiple linear regression analysis, we respectively deal with daily maximum load and daily minimum load and daily average load and the relationship between meteorological factors and regression analysis, to get the regression coefficients and residual standard deviation of equation. Combined with the regression coefficient, we get a different degree of the meteorological factors influence on the load, and determine the forecasting meteorological factors to improve the accuracy.

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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TY  - CONF
AU  - Jingyao Wang
PY  - 2017/04
DA  - 2017/04
TI  - Power system short-term load forecasting
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 250
EP  - 253
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.49
DO  - 10.2991/icmmct-17.2017.49
ID  - Wang2017/04
ER  -