Short-Term Bus Load Matching and Forecasting Model
Ran Li, Chenjun Sun, Yang Liu, Lilin Peng, Ming Zeng
Available Online September 2016.
- https://doi.org/10.2991/iccia-16.2016.23How to use a DOI?
- Short-term bus load forecasting; Least squares support vector machine (LSSVM); Matching model; Subtractive clustering.
- Bus load forecasting is the foundation to make power grid to be secure, economic and efficient, and also is the concrete measure and effective way to promote national energy saving and emissions reduction. Based on daily load curve of typical areas, and by means of subtractive clustering, the regional bus load was classified and bus load matching model was constructed. Furthermore, bus load forecasting model with the least squares support vector machine model (LSSVM) was put forward. Finally, the validity of load matching and forecasting model was verified by numerical examples.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Ran Li AU - Chenjun Sun AU - Yang Liu AU - Lilin Peng AU - Ming Zeng PY - 2016/09 DA - 2016/09 TI - Short-Term Bus Load Matching and Forecasting Model BT - 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016) PB - Atlantis Press SP - 120 EP - 124 SN - 2352-538X UR - https://doi.org/10.2991/iccia-16.2016.23 DO - https://doi.org/10.2991/iccia-16.2016.23 ID - Li2016/09 ER -