Short-term Load Forecasting of Local Power Grid Based on Support Vector Machine

DOI

10.2991/emcs-17.2017.351How to use a DOI?

Keywords

Short term load forecasting; SVM; Prediction accuracy; Normalize.

Abstract

Short term load forecasting is an important basic work for power system planning and scheduling, short term load forecasting method based on SVM is adopted in this paper, through analyze the factors that influence the load forecasting and normalize the factors which influence the load forecasting. Using the historical load data of a city in Yunnan as the training data, the results show that the method can improve the prediction accuracy to a certain extent.

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  - Jing Hua
AU  - Wei Xiong
AU  - Yanping Zhou
PY  - 2017/03
DA  - 2017/03
TI  - Short-term Load Forecasting of Local Power Grid Based on Support Vector Machine
BT  - Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)
PB  - Atlantis Press
SP  - 1851
EP  - 1856
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-17.2017.351
DO  - 10.2991/emcs-17.2017.351
ID  - Hua2017/03
ER  -