| Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 5 | |
| Section | Modeling, Analysis, and Simulation of Intelligent Manufacturing Processes | |
| DOI | https://doi.org/10.1051/matecconf/201817301007 | |
| Published online | 19 June 2018 | |
Short-term Load Forecasting Model for Microgrid Based on HSA-SVM
1
Qingdao Electric Power Company, 266002, Qingdao, Shandong Province, China
2
Qingdao University, 266071, Qingdao, Shandong Province, China
3
Tianjin University, Key Laboratory of Smart Grid of Ministry of Education, 300072, Tianjin, China
* Corresponding author : slnzzs@126.com
Short-term load forecasting for microgrid is the basis of the research on scheduling techniques of microgrid. Accurate load forecasting for microgrid will provide the necessary basis for cooperative optimization scheduling. Short-term loadforecasting model for microgrid based on support vector machine(SVM) is constructed in this paper. The harmony search optimization algorithm(HSA) is used to optimize the parameters of the SVM model, because it has the advantages of fast convergence speed and better optimization ability. Through the simulation and test of the actual microgrid load system, it is proved that the short-term loadforecasting model for microgrid based on HSA-SVM can effectively improve the prediction accuracy.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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