MATEC Web Conf.
Volume 173, 20182018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|Number of page(s)||5|
|Section||Modeling, Analysis, and Simulation of Intelligent Manufacturing Processes|
|Published online||19 June 2018|
Short-term Load Forecasting Model for Microgrid Based on HSA-SVM
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 : firstname.lastname@example.org
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.