Short-Term Bus Load Matching and Forecasting Model

DOI

10.2991/iccia-16.2016.23How to use a DOI?

Keywords

Short-term bus load forecasting; Least squares support vector machine (LSSVM); Matching model; Subtractive clustering.

Abstract

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.

Copyright

© 2016, 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  - 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  - Proceedings of the 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  - 10.2991/iccia-16.2016.23
ID  - Li2016/09
ER  -