Short Term Load Forecasting of Power System
Available Online July 2016.
- https://doi.org/10.2991/iccia-17.2017.126How to use a DOI?
- Load forecasting, meteorological factors, BP neural network, similar days.
- In this paper, short-term load forecasting of power system considering meteorological factors is studied. The power system load is divided into three parts: basic component, weather sensitive component and random component. Then the correction strategy of similar days is introduced and the meteorological factors is considered to improve the original BP model. And the similar days are determined according to the periodic characteristic of the load value and the grey relational analysis. Finally, by comparing the predicted data with the actual data, it is proved that the prediction model agrees with the actual situation and has higher prediction accuracy.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jiahui Fan PY - 2016/07 DA - 2016/07 TI - Short Term Load Forecasting of Power System BT - 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017) PB - Atlantis Press SP - 728 EP - 731 SN - 2352-538X UR - https://doi.org/10.2991/iccia-17.2017.126 DO - https://doi.org/10.2991/iccia-17.2017.126 ID - Fan2016/07 ER -