Time-of-use Short-term Load Prediction Model Based on Variable Step Size Optimized HBMO-LS-SVM Method in Day-head Market

DOI

10.2991/febm-16.2016.49How to use a DOI?

Keywords

time-of-use short-term load prediction; variable step size optimization; HBMO-LS-SVM algorithm

Abstract

The short-term load prediction results are important basis for arranging dispatching plans scientifically, decision-making for competitive bidding of power generation enterprises and users. Firstly, this paper constructs a factor index system of time-of-use short-term load prediction of next day in day-head market, and then builds the HBMO-LS-SVM prediction model. In order to prevent falling into local optimum traps, it optimizes the prediction model based on variable step size, which can improve the convergence speed of prediction as well as prediction accuracy in principle.

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  - Guo Lei
AU  - Xue Song
AU  - Liu Yang
AU  - Zeng Ming
PY  - 2016/11
DA  - 2016/11
TI  - Time-of-use Short-term Load Prediction Model Based on Variable Step Size Optimized HBMO-LS-SVM Method in Day-head Market
BT  - Proceedings of the First International Conference Economic and Business Management 2016
PB  - Atlantis Press
SP  - 324
EP  - 328
SN  - 2352-5428
UR  - https://doi.org/10.2991/febm-16.2016.49
DO  - 10.2991/febm-16.2016.49
ID  - Lei2016/11
ER  -