Title :
Day-ahead electricity price prediction based on multiple ELM
Author :
Tian, Huixin ; Meng, Bo ; Wang, Shuzhou
Author_Institution :
Sch. of Electr. Eng. & Autom., Tianjin Polytech. Univ., Tianjin, China
Abstract :
Aiming at the characters of day-ahead electricity price, an electricity price prediction model is established by combining the intelligent modeling methods. A new neural network method ELM is selected for its better performance to establish the basic day-ahead electricity price prediction model. Using the information fusion and ensemble ideas, a multiple ELM modeling approach is proposed to establish the prediction model. The day-ahead electricity price prediction model is tested by the real data. The experiments demonstrate that the new prediction model established by the new method has better performance.
Keywords :
learning (artificial intelligence); neural nets; power engineering computing; power markets; day-ahead electricity price prediction; extreme learning machine; intelligent modeling methods; multiple ELM network; neural network method; Automation; Econometrics; Feedforward neural networks; Joining processes; Machine learning; Neural networks; Power markets; Power system modeling; Predictive models; Statistical analysis; ELM; electricity market; electricity price prediction; neural network;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5499079