Algorithm Optimization of Short-Term Load Forecasting Model Based on Least Square Support Vector Machine

Author(s):  
Yuh-Chung Lin ◽  
Shusen Kuang ◽  
Kuo-Chi Chang ◽  
Hui-Qiong Deng ◽  
Fu-Hsiang Chang ◽  
...  
2018 ◽  
Vol 173 ◽  
pp. 01007
Author(s):  
Han Aoyang ◽  
Yu Litao ◽  
An Shuhuai ◽  
Zhang Zhisheng

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.


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